Author: Jeroen

[blog] Can We Plan Slow – But Steady – Growth for Critical Studies?

Author: Charlotte Ryan (University of Massachusetts, Lowell/Movement-Media
Research Action Project), member of the DATACTIVE ethics board.

This is a response post to the blog ‘Tech, data and social change: A plea for cross-disciplinary engagement, historical memory, and … Critical Community Studies‘ written by Kersti Wissenbach.

To maximize technologies’ value in social change efforts, Kersti Wissenbach urges researchers to join with communities facing power inequalities to draw lessons from practice. In short, the liberating potential of technologies for social change cannot be realized without holistically addressing broader inequalities. Her insights are many, in fact, communication activists and scholars could use her blog as a guide for ongoing conversations. Three points especially resonate with my experiences as a social movement scholar/activist working in collaboration with communities and other scholars:

  • Who is at the table?
    Wissenbach stresses the critical role of proactive communities in fostering technologies for social change as a corrective to the “dominant civic tech discourse [that] seems to keep departing from the ‘tech’ rather than the ‘civic’.” She stresses that an inclusive “we” emerges from intentional and sustained working relationships.
  • Power (and inequalities of power) matter!
    Acknowledging that technologies’ possibilities are often shaped long before many constituencies are invited to participate, Wissenbach asks those advancing social change technologies to notice the creation and recreation of power structures:
    “Only inclusive communities,” she cautions, “can really translate inclusive technology approaches, and consequently, inclusive governance.”
  • Tech for social change needs critical community studies
    Wissenbach calls for the emergence of critical community studies that—as do critical development, communication, feminist, and subaltern studies–crosses disciplines, “taking the community as an entry point in the study of technology for social change.” Practitioners and scholars would reflect together to draw and disseminate shared lessons from experience. This would allow “communities, supposed to benefit from certain decisions, [to] have a seat on the table.”

Anyone interested in the potential of civic tech—activists, scholar-activists, engineers, designers, artists, or other social communication innovators—will warmly welcome Wissenbach’s vision of Critical Community Studies. She proposes not another sub-specialty with esoteric journals and self-referential jargon, but a research network of learning communities expanding conceptual dialogs across the usual divides. And, she recognizes the urgent need to preserve and broadly disseminate learning about technologies for social change.

I agree but cautiously. It is just what’s needed. But the academy tends to resist engaged scholarship. We need to think about where to locate transformative theory-building; sadly, calls to break with traditional research approaches may be more warmly received outside academic institutions than within. The academy itself, at least in the United States, is under duress. How would Critical Community Studies explain itself to academic institutions fascinated by brand, market niche, and revenue streams? Critical Community Studies is not likely to be a cash cow generating more profits faster, and with less investment. The U.S. trend to turn education into a profit-making industry may be extreme, but it raises the need to look before we leap.

Like Wissenbach, I entered the academy with deep roots in social movements and community activism. Like her, I want the academy to produce knowledge and technology for the social good. Like her, I want communities directly affected to be fully vested in all phases of learning. Like her, I am eager to move beyond vague calls for participation and inclusion. My experiences to date, however, give me pause for thought.

button life

Caption: Thirty years in buttons

In the mid-1980’s, I was among a dozen established and emerging scholars who formed the university-based Media Research Action Project (MRAP). We were well-positioned to bridge the theorist-practitioner divide; many of us had begun as movement activists and we had ties to practitioners. This made it easier for MRAP to work with under-represented and misrepresented communities and constituencies to identify and challenge barriers to democratic communication and to build communication capacity.

U.S. based social movements face recurring challenges: our movements hemorrhage learning between generations; we still need to grapple with the legacies of slavery, colonialism and jingoism; our labor movement has withered. Living amidst relative plenty, U.S. residents may feel far removed from crises elsewhere. Competitive individualism, market pressures, and dismantled social welfare programs leave U.S. residents feeling precarious —even if we embrace liberatory ideals.

In light of these material conditions, MRAP wanted to broaden political dialogs about equality and justice. At first, we focused on transferring communication skills—one and two-day workshops. We soon realized that we needed ongoing working relationships to test strategies, build infrastructure and shared conceptual frameworks. But it took years to find the funds to run a more sustained program. Foundations—even when they liked our work—wanted us to ‘scale up’ fast (one national foundation asked us to take on 14 cities). In contrast, we saw building viable working relations as labor-intensive and slow. One U.S. federal agency offered hefty funding for proposals to “bridge the digital divide.” MRAP filed a book-length application with ten community partner organizations, eight in communities of color. The agency responded positively to MRAP’s plan, they urged us to resubmit but asked that we dump our partners and replace them with mainstream charities, preferably statewide.

And so the constraints tightened. Government and foundations’ preference for quick gains could marginalize (again) the very partners MRAP formed to support. To support ourselves, we could take day jobs, but this limited our availability. Over and over, we found—at least in the U.S. context—talk of addressing power inequalities far exceeded public will and deeds. Few mainstream institutions would commit the labor, skill, and time to reduce institutionalized power inequalities. Nor did they appreciate that developing shared lessons from practical experiences is labor intensive. (Wissenbach notes a number of these obstacles).

Despite all of the above, MRAP and our partners had victories. One neighborhood collaboration took over local political offices; another defeated an attempt to shut down an important community school; others passed legislation; and made common cause with the Occupy Movement to challenge the demonization of poor people in America. We won…sometimes. More often, we lost but lived to fight another day. And we helped document the ups and downs of our social movements. It was enormous fun even when it was really hard. As the designated holders and tellers of these histories, MRAP participants deepened our understanding of the macro-mezzo-micro interplay of political, social, economic, and cultural power.

From hundreds of conversations, dozens of collaborations, and gigabytes of notes, case studies, and foundation proposals, came a handful of collaborations that advanced our understanding of how U.S. movement organizations synchronize communication, political strategizing, coalition building, and leader and organizational development, and how groups integrate learning into ongoing campaigns.

We have begun to upload MRAP’s work at www.mrap.info. But those pursuing a transformed critical research tradition, should acknowledge that the academy has resisted grounded practice, and that the best critical reflections were often led by activists outside the academy rooted in communities directly facing power inequalities. In light of this, Wissenbach’s insistence that communities directly affected “be at the table” becomes an absolute.

Let me turn to Critical Communication Studies more specifically. To maximize publishing, U.S. scholars tend to communicate within, not across, disciplines. Anxious regarding slowing their productivity, they tend to avoid the unpredictability of practical work. For their part, the civic tech networks and communities facing inequalities find themselves competing for resources, a competition that can undermine the very collaborations they want to build. Even if resources are located, efforts may fade if a grant ends or a government changes hands.

So while I welcome the call for researchers to join practitioners in designing mutually beneficial projects, I want to do it right and that may mean do it slow. First off, who is the “we/us” mentioned twenty times by Wissenbach (or an equal number of times by me)? We need a real “we”: transforming institutional practices and priorities whether in academic or communication systems is a collective process. An aggregate of individuals even if they share common values does not constitute “us,” social movements as dialogic communities that consider, test, and unite around strategies. (As Wissenbach underscores, “we” need to shift power, and this requires shared strategies, efficient use of sustainable resources, and a capacity to learn from experience).

In short, transforming scholarly research from individual to collective models will take movement building. A first step may be recognizing that “we” needs to be built. Calling “we” a social construction does not mean it’s unreal; it means it’s our job to make it real.

Conclusion

I share Wissenbach’s respect for past and present efforts to lessen social inequalities via communication empowerment. I agree that “only inclusive communities can really translate inclusive technology approaches and, consequently, inclusive governance.” And I know that this will be hard to achieve. Progress may lie ahead but precarity and heavy work lie ahead as well. A beloved friend says to me these days, “Getting old is not for the faint of heart.” Neither is movement building.

 

Bibliography:

Howley, K. (2005). Community media: people, places, and communication technologies. Cambridge, UK ; New York : Cambridge University Press.

Kavada, A. (2010). Email lists and participatory democracy in the European social forum. Media, Culture & Society, 32(3), 355. doi: 10.1080/13691180802304854

Kavada, A. (2013). Internet cultures and protest movements: The cultural links between strategy, organizing and online communication. In B. Cammaerts, A. Mattoni & P.

McCurdy (Eds.), Mediation and protest movements (pp. 75–94). Bristol, England: Intellect.

Kidd, D., Barker-Plummer, B., & Rodriguez, C. (2005). Media democracy from the ground up: mapping communication practices in the counter public sphere. Report to the Social Science Research Council. New York

Kidd, D., Rodriguez, C., & Stein, L. (2009). Making our media: Global initiatives toward a democratic public sphere. Cresskill: Hampton Press.

Lentz, R. G., & Oden, M. D. (2001). Digital divide or digital opportunity in the Mississippi Delta region of the US. Telecommunications policy, 25(5), 291-313.

Lentz, R. G. Regulation as Linguistic Engineering. (2011). The Handbook of Global Media and Communication Policy, 432-448. IN Mansell, R., & Raboy, M. (Eds.) (Vol. 6). John Wiley & Sons.

Magallanes-Blanco, C., & Pérez-Bermúdez, J. A. (2009). Citizens’ publications that empower: social change for the homeless. Development in practice, 19(4-5), 654-664.

Mattoni, A. (2016). Media practices and protest politics: How precarious workers mobilise. Routledge.

Mattoni, A., & Treré, E. (2014). Media practices, mediation processes, and mediatization in the study of social movements. Communication theory, 24(3), 252-271.

Milan, S. (2009). Four steps to community media as a development tool. Development in Practice, 19(4-5), 598-609.

Rubin, N. (2002). Highlander media justice gathering final report. New Market, TN: Highlander Research and Education Center.

Treré, E. and Magallanes-Blanco, C. (2015) Battlefields, Experiences, Debates: Latin American Struggles and Digital Media Resistance, International Journal of Communication 9: 3652–366.

annual DATACTIVE PhD Colloquium, May 4th

Date: Tomorrow, May 4th 13.30

Location: Oudemanhuispoort 4-6, Amsterdam, room OMHP-E0.12

Tomorrow we will have our yearly PhD colloquium, a moment to showcase our work and receive feedback. You’re invited to join us.

This year’s guests, acting as respondents, are Marlies Glasius (Amsterdam School for Social Science Research) and Annalisa Pellizza (University of Twente). Our new postdoctoral fellow Fabien Cante will be also be in attendance.

The program is as follows:

(13:30 – 14:15) Niels ten Oever: “The evolving notion of the public interest in the Internet architecture”

(14:20 – 15:05) Kersti Wissenbach: “Accounting for Power in a Datafied World: A Social Movement Approach to Civic Tech Activism”

(15:10 – 15:25) Coffee Break

(15:25 – 16:10) Becky Kazansky: “Infrastructures of Anticipation: civil society strategies in an age of ubiquitous surveillance”

(16:15 – 17:00) Guillen Torres: “Empowering information activists through institutional resistance”.

 

Welcome to two new team members: Hoang & Fabien

DATACTIVE is happy to welcome two new team members!

Fabien Cante will join us as a postdoc, mostly to help with empirical research. Fabien is interested in media as contested infrastructures of city life. His PhD (London School of Economics, 2018) work was grounded in Abidjan, Côte d’Ivoire; he hopes to continue asking what datafication means in an African metropolis. In addition to academic work, Fabien is comms officer for the Migrants’ Rights Network and active in neighbourhood struggles in South London.

IMG_20180422_171539

 

We are also happy to have Hoang joining us to help us out with our empirical research practices as a part of her rMA studies.

Tu Quynh Hoang has a BA in Professional Communication from RMIT University. Concerned about human rights issues in Asia, she moved from working in media companies to doing research on Internet controls and citizens’ media. She is currently studying towards a Research MA in Media Studies at the University of Amsterdam.

Quynh profile photo

Welcome both, we are very much looking forward to working with you!

[blog 2/3] Designing the city by numbers? Digital quantification regimes of cycling mobility 1

 

 

This is the second of three blog posts of the series ‘Designing the city by numbers? Bottom-up initiatives for data-driven urbanism in Santiago de Chile’, by Martín Tironi and Matías Valderrama Barragán. Find the first post here. Stay tuned: the next episode will appear next Friday, May 4th!

 

Over the past two years, we have been studying cases that specifically involve digital quantification and urban cycling in the city of Santiago. Because of the multiple benefits to the environment, urban congestion, and citizens’ health, urban cycling has been characterized as a “green” and “sustainable” form of mobility, highly attractive for smart cities initiatives. Under this trend, various digital devices and self-tracking apps have been developed for quantifying and expand urban cycling. The numbers and data generated by such an array of technologies have more recently been reframed as valuable crowdsourced information to inform and guide decisions on urban planning and promoting citizen demands. In this sense, data-driven initiatives seem to promote a spirit where citizens themselves appear as the central actors of urban planning thanks to the development of these civic technologies. In contrast, we explore why we should remain sceptical of how such data-driven initiatives adopt what can appear to be bottom-up approaches. We should remain critically vigilant of how such moves can be used to promote market-driven technological adoption and low-efforts forms of citizenship instead.

RUBI: Let the bikes speak for themselves

Our first example is the case of RUBI, Urban Bike Tracker device in Spanish, which we examined more in detail in a recently published paper in the journal Environment and Planning D. This device records the routes taken by cyclists anonymously in a georeferenced database that is later processed on a web platform (RubiApp) to obtain numbers, metrics and visualizations of the users. It was developed in 2014 by a young engineering student as his undergraduate thesis. At that time, he started a bottom-up project called Stgo2020, in order to invite cyclists of Santiago to voluntarily participate in the collection of data about their everyday trips, and with that, challenging the status quo in urban planning and allowing cyclists to act as “co-designers” of their own city. The project achieved the collection of data from a hundred volunteer cyclists, generating graphics, tables and heat maps about urban cycling. This information was shared later with the Transportation Office hoping that it would help to make data-driven decisions about future cycling lanes -but he never knew if the data was used in some way.

Because of the academic origin of RUBI, the entire development of the device was based on a strongly scientific narrative on how to achieve a “representative” and “clean” sample of cyclists’ mobility. So, the developer decided to design a hardware that could be differentiated from apps like STRAVA and wearables technologies that would depend on expensive technologies and data plan, presenting strong biases in his opinion. This scientific narrative marked the whole design and materiality of the RUBI. The first prototypes were large, fragile and very much dependent on the human user in several respects. In fact, the engineer behind the device playfully drew a human face on the first prototype. But several problems emerged with these first versions. For example, users continually forgot to turn it on or off when necessary, some users subvert and appropriate the functioning of the technology in unexpected ways, and particular problems emerged from the GPS of the device itself. These emerging breakdowns from the everyday entanglement of cyclists, devices, bicycles and urban spaces, produced “erroneous”, “stupid” or “absurd” data for the engineer, that we call it as “idiotic data” in our paper based on Isabelle Stengers conceptual character of the idiot, which slow down and put in question the “clean” collection of data intended for the project. To confront the emergence of idiotic data, new sensors, algorithms and automated functions were aggregated to give the device a greater “smartness” to operate as an autonomous and independent entity, outside of human control. In the process, the device shift to a literal “black box” ensuring little interaction with the cyclists and the environment as possible, and as a result, the practice of quantifying the urban cycling become more unnoticed and effortless for cyclists.

During 2016, the RUBI device scaled up to other cities using new business models, losing its bottom-up nature. The company RubiCo was created and reached agreements with local governments and international consulting agencies like the Inter-American Development Bank, to map the use of public bicycle rental systems -even without the notice of users in some cases. Giving the device “true intelligence” was not only a precautionary “solution” to idiotic data, but it was mobilized to add value and solidity to the regime compared to the competition. In contrast to other self-tracking technologies (apps, wearables, etc.), RubiCo focuses on control the biases and noise of the sample on cyclists’ mobility, constituting RUBI interaction with the bike as an authentic “moving laboratory” that captures georeferenced data precisely and objectively, using the words of RUBI’s developer.

Stay tuned for the final posts in this series for more on the development of the KAPPO pro-cycling smartphone game and its outcomes in Santiago.

 

 

1. This text is based on a presentation at the Workshop “Designing people by numbers” held in Pontificia Universidad Católica in November 2017, with the participation of Celia Lury

 

About the authors

Martín Tironi is Associate Professor, School of Design at the Pontifical Catholic University of Chile. He holds a PhD from Centre de Sociologie de l’Innovation (CSI), École des Mines de Paris, where he also did post-doctorate studies. He received his Master degree in Sociology at the Université Paris Sorbonne V and his BA in Sociology at the Pontifical Catholic University of Chile. Now he’s doing a visiting Fellow (2018) in Centre of Invention and Social Proces, Goldsmiths, University of London [email: martin.tironi@uc.cl]

Matías Valderrama Barragán is a sociologist with a Master in Sociology from the Pontifical Catholic University of Chile. He is currently working in research projects about digital transformation of organizations and datafication of individuals and environments in Chile. [email:mbvalder@uc.cl]

[blog] #Data4Good, Part II: A necessary debate

By Miren Gutiérrez*
In the context of the Cambridge Analytica scandal, fake news, the use of personal data for propagandistic purposes and mass surveillance, the Postgraduate Programme “Data analysis, research and communication” proposed a singular debate on how the (big) data infrastructure and other technologies can serve to improve people’s lives and the environment. The discussion was conceived as the second part of an ongoing conversation that started in Amsterdam with the Data for the Social good conference in November 2017.

We understand that four communities converge in the realisation of data projects with social impact: organisations that transfer skills, create platforms and tools and generate opportunities; the catalysts, which provide the funds and the means; those that produce data journalism, and the data activists. However, on rare occasions we see them debate together in public. Last April 12, at the headquarters of the Deusto Business School in Madrid, we met with representatives of these four communities, namely:

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(From left to right, see picture), Adolfo Antón Bravo, head of the DataLab at Medialab-Prado, where he has led the experimentation, production and dissemination of projects around the data culture and the promotion of open data. Adolfo has also been representative of the Open Knowledge Foundation Spain, a catalyst organisation dedicated to finance and promote data projects, among others.

Mar Cabra, a well-known investigative journalist specialising in data analysis, who has been in charge of the Data and Research Unit of the International Consortium of Investigative Journalists (ICIJ), winner of the 2017 Pulitzer Prize with the investigation known as “The Papers of Panama”.

Juan Carlos Alonso, designer at Vizzuality, an organisation that offers applications that help to understand data through its visualisation better and comprehend global processes such as deforestation, disaster preparedness, the global flow of trade in agricultural products or action against climate change around the world.

Ignacio Jovtis, head of Research and Policies of Amnesty International Spain. AI uses testimonies, digital cartography, data and satellite photography to denounce and produce evidence of human rights abuses, for example in the war in Syria and the military appropriation of Rohingya land in Myanmar.

And Juanlu Sánchez, another well-known journalist, co-founder and deputy director of eldiario.es, who specialises in digital content, new media and independent journalism. Based on data analysis, he has led and collaborated in various investigative stories rocking Spain, such as the Bankia scandal.

The prestigious illustrator Jorge Martín facilitated the conversation with a 3.5×1 m mural summarising the main issues tackled by the panellists and the audience.

deusto

The conference’s formula was not conventional, as the panellists were asked not to offer a typical presentation, but to engage in a dialogue with the audience, most of whom belonged to the four communities mentioned earlier, representing NGOs, foundations, research centres and news media organisations.

Together, we talked about:

• the secret of successful data projects combining a “nose for a good story”, legwork (including hanging out in bars) and data in sufficient quantity and quality;
• the need to merge wetware and algorithms;
• the skills gaps within organisations;
• the absolute necessity to collaborate to tackle datasets and issues that are too big to handle alone;
• the demand to engage funders at all level –from individuals to foundations— to make these projects possible;
• the advantages of a good visualisation for both analysis and communication of findings;
• where and how to obtain data, when public data is not public much less open;
• the need for projects of any nature to have real social impact and shape policy;
• the combination of analogic methodologies (i.e. interviews, testimonies, documents) with data-based methodologies (i.e. satellite imagery, interactive cartography and statistics), and how this is disrupting humanitarianism, human rights and environmental campaigning and newsrooms;
• the need to integrate paper archives (i.e. using optical recognition systems) to incorporate the past into the present;
• the magic of combining seemingly unrelated datasets;
• the imperative to share not only datasets but also code, so others can contribute to the conversation, for example exploring venues that were not apparent to us;
• the importance of generating social communities around projects;
• the blurring of lines separating journalism, activism and research when it comes to data analysis;
• the experiences of using crowds, not only to gather data but also to analyse them.

Cases and issues discussed included Amnesty’s “troll patrol”, an initiative to assign digital volunteers to analyse abusive tweets aimed at women, and investigation on the army appropriation of Rohingyas’ land in Myanmar based on satellite imagery; Trase, a Vizzuality project that tracks agricultural trade flows (including commodities such as soy, beef and palm oil), amazingly based both on massive digitalised datasets and the paper trail left by commodities in ports; the “Panama papers”, and the massive collaborative effort that involved analysing 2,6 terabytes of data, and 109 media outlets in 76 countries; the successful diario.es business model, based on data and investigative journalism and supported by subscribers who believe in independent reporting; and the Datalab’s workshops, focused on data journalism and visualisation, which have been going on for six years now and have given birth to projects still active today.

The main conclusions could be summarised as follows:

1) the human factor –wetware— is as essential for the success of data projects with social impact as software and hardware, since technology alone is not a magic bullet;
2) the collaboration of different actors from the four communities with different competencies and resources is essential for these projects to be successful and to have an impact; and
3) a social transformation is also needed within non-profit and media organisations so that the culture of the data spreads far and away, and the data infrastructure is maximised for the transformation of the whole society and the conservation of nature.

* Dr Miren Gutiérrez is the director of the postgraduate Programme “Data analysis, research and communication” at the University of Deusto and a Lecturer on Communication. She is also a Research Associate at Datactive.

[blog] Critical reflections on FAT* 2018: a historical idealist perspective

Author: Sebastian Benthall, Research Scientist at NYU Steinhardt and PhD Candidate UC Berkeley School of Information.

In February, 2018, the inaugural 2018 FAT* conference was held in New York City:

The FAT* Conference 2018 is a two-day event that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems. This inaugural conference builds on success of prior workshops like FAT/ML, FAT/Rec, DAT, Ethics in NLP, and others.

FAT stands for “Fairness, Accountability, Transparency”, and the asterisk, pronounced “star”, is a wildcard character, which indicates that the conference ranges more widely that earlier workshops it succeeds, such as FAT/ML (ML meaning, “machine learning“), FAT/Rec (Rec meaning “recommender systems“). You might conclude from the amount of geekery in the title and history of the conference that FAT* is a computer science conference.

You would be half right. Other details reveal that the conference has a different, broader agenda. It was held at New York University’s Law School, and many of the committee chairs are law professors, not computer science professors. The first keynote speaker, Latanya Sweeney, argued that technology is the new policy as more and more decisions are delegated to automated systems. The responsibility of governance, it seems, is falling to the creators of artificial intelligence. The keynote speaker on the second day was Prof. Deborah Hellman, who provided a philosophical argument for why discrimination is morally wrong. This opened into a conversation about the relationship between random fate and justice with computer scientist Cynthia Dwork. The other speakers in the program in one way or another grappled with the problem of how to responsibly wield technological power over society.

It was a successful conference and it has great promise as venue for future work. It has this promise because it has been set up to expand intellectually beyond the confines of the current state of discourse around accountability and automation. This post is about the tensions within FAT* that make it intellectually dynamic. FAT* reflects the conditions of our a particular historical, cultural, and economic moment. The contention of this post is that the community involved in the conference has the opportunity to transcend that moment if they encounter its own contradictions head-on through praxis.

One significant tendency among the research at FAT* was the mathematization of ethics. Exemplified by Menon and Williamson’s “The cost of fairness in binary classification” (2018) (winner of a best paper award at the conference), many researchers come to FAT* to translate ethical injunctions, and the tradeoffs between them, into mathematical expressions. This striking intellectual endeavor sits at the center of a number of controversies between the humanities and sciences that have been going on for decades and continue today.

As has been long recognized in the foundational theory of computer science, computational algorithms are powerful because the are logically equivalent to the processes of mathematical proof. Algorithms, in the technical sense of the term, can be no more and no less powerful than mathematics itself. It has long been a concern that a world controlled by algorithms would be an amoral one; in his 1947 book Eclipse of Reason, Max Horkheimer argued that the increasing use of formal reason (which includes mathematics and computation) for pragmatic purposes would lead to a world dominated by industrial power that was indifferent to human moral considerations of what is right or good. Hannah Arendt, in The Human Condition (1959), wrote about the power of scientists who spoke in obscure mathematical language and were therefore beyond the scrutiny of democratic politics. Because mathematics is universal, it is unable to express political interests, which arise from people’s real, particular situations.

We live in a strikingly different time from the mid-20th century. Ethical concerns with the role of algorithms in society have been brought to trained computer scientists, and their natural and correct inclination has been to determine the mathematical form of the concern. Many of these scholars would sincerely like to design a better system.

Perhaps disappointingly, all the great discoveries in foundations of computing are impossibility results: the Halting Problem, the No Free Lunch theorem, etc. And it is no different in the field of Fairness in Machine Learning. What computer scientists have discovered is that life isn’t, and can’t be, fair, because “fairness” has several different definitions (twenty-one at last count) that are incompatible with each other (Hardt et al., 2016; Kleinberg et al., 2016). Because there are inherent tradeoffs to different conceptions of fairness and any one definition will allocate outcomes differently for different kinds of people, the question of what fairness is has now been exposed as an inherently political question with no compelling scientific answer.

Naturally, computer scientists are not the first to discover this. What’s happened is that it is their turn to discover this eternal truth because in this historical moment computer science is the scientific discipline that is most emblematic of power. This is because the richest and most powerful companies, the ones almost everybody depends on daily, are technology companies, and these companies project the image that their success is do mainly to the scientific genius of their early employees and the quality of the technology that is at their operational core.

The problem is that computer science as scientific discipline has very little to do with why large technology companies have so much power and sometimes abuse that power. These companies are much more than their engineers; they also include designers, product managers, salespeople, public relations people, and of course executives and shareholders. As sociotechnical organizations, they are most responsive to the profit motive, government regulations, and consumer behavior. Even if being fair was technically possible, they would still be businesses with very non-technical reasons for being unfair or unaccountable.

Perhaps because these large companies are so powerful, few of the papers at the conference critiqued them directly. Instead, the focus was often on the software systems used by municipal governments. These were insightful and important papers. Barabas et al.’s paper questioned the assumptions motivating much of the inquiry around “fairness in machine learning” by delving into the history and ideology of actuarial risk assessment in criminal sentencing. Chouldechova et al.’s case study in the workings of a child mistreatment hotline (winner of a best paper award) was a realistic and balanced study of the challenges of operating an algorithmic risk assessment system in municipal social services. At its best, FAT* didn’t look much like a computer science conference at all, even when the speakers and authors had computer science training. At its best, FAT* was grappling towards something new.

Some of this grappling is awkward. Buolamwini and Gebru presented a technically and politically interesting study of how commercially available facial recognition technologies underperform on women, on darker-skinned people, and intersectionally on darker-skinned women. In addition to presenting their results, the speakers proudly described how some the facial recognition companies responded to their article by improving the accuracy of their technology. For some at the conference, this was a victory for fairer representation and accountability of facial recognition technology that was otherwise built to favor lighter skinned men. But others found it difficult to celebrate the improved effectiveness of a technology for automated surveillance. Out of context, it’s impossible to know whether this technology does good or ill to those wearing the faces it recognizes. What was presented as a form of activism against repressive or marginalizing political forces may just as well have been playing into their hands.

This political ambiguity was glossed over, not resolved. And therein lay the crux of the political problem at the heart of FAT*: it’s full of well-intentioned people trying to discover technical band-aids to what are actually systemic social and economic problems. Their intentions and their technical contributions are both laudable. But there was something ideologically fishy going on, a fishiness reflective of a broader historical moment. Nancy Fraser (2016) has written about the phenomenon of progressive neoliberalism, an ideology that sounds like an oxymoron but in fact reflects the alliance between the innovation sector and identity-based activist movements. Fraser argues that progressive neoliberalism has been a hegemonic force until very recently. This year FAT*, with its mainly progressive sense of Fairness and Accountability and arguably neoliberal emphasis on computational solutions, was a throwback to what for many at the conference was a happier political time. I hope that next year’s conference takes a cue from Fraser and is more critical of the zeitgeist.

For now, as form of activism that changes things for the better, this year’s conference largely fell short because it would not address the systemic elephants in the room. A dialectical sublation is necessary and imminent. For it to do this effectively, the conference may need to add another letter to its name, representing another value. Michael Veale has suggested that the conference add an “R”, for reflexivity, perhaps a nod to the cherished value of critical qualitative scholars, who are clearly welcome in the room. However, if the conference is to realize its highest potential, it should add a “J”, for justice, and see what the bright minds of computer science think of that.

References

Arendt, Hannah. The human condition:[a study of the central dilemmas facing modern man]. Doubleday, 1959.

Barabas, Chelsea, et al. “Interventions over Predictions: Reframing the Ethical Debate for Actuarial Risk Assessment.” arXiv preprint arXiv:1712.08238 (2017).

Buolamwini, Joy, and Timnit Gebru. “Gender shades: Intersectional accuracy disparities in commercial gender classification.” Conference on Fairness, Accountability and Transparency. 2018.

Chouldechova, Alexandra, et al. “A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions.” Conference on Fairness, Accountability and Transparency. 2018.

Fraser, Nancy. “Progressive neoliberalism versus reactionary populism: A choice that feminists should refuse.” NORA-Nordic Journal of Feminist and Gender Research 24.4 (2016): 281-284.

Hardt, Moritz, Eric Price, and Nati Srebro. “Equality of opportunity in supervised learning.” Advances in Neural Information Processing Systems. 2016.

Hellman, Deborah. “Indirect Discrimination and the Duty to Avoid Compounding Injustice.” (2017).

Horkheimer, Max. “Eclipse of Reason. 1947.” New York: Continuum (1974).

Kleinberg, Jon, Sendhil Mullainathan, and Manish Raghavan. “Inherent trade-offs in the fair determination of risk scores.” arXiv preprint arXiv:1609.05807 (2016).

Miren Gutierrez presents “Datos para la transformación social” (Madrid, April 12)

DATACTIVE Research Associate Miren Gutierrez organised a follow-up of the ‘Data for the Social Good’ event (Amsterdam, November 2017). The debate will take place in Madrid on Thursday the 12th of April. You can check out the impressive line-up in the description of the event (in Spanish).

Cuándo: 12 de abril, jueves, de 16:00 a 18:00

Dónde: Sede de la Deusto Business School, calle Castelló, 76, Madrid

Cuatro comunidades confluyen con frecuencia en la realización de proyectos de datos con impacto social: las organizaciones que transfieren habilidades, crean plataformas y herramientas, y generan oportunidades de encuentro; las catalizadoras, que proporcionan los fondos y los medios; las que producen periodismo de datos, y las activistas. Sin embargo, en pocas ocasiones las vemos debatir juntas en público.

Te proponemos una conferencia, organizada por el Programa “Análisis, investigación y comunicación de Datos” de la Universidad de Deusto, que sienta en un panel a representantes de estos cuatro grupos para hablar de cómo pueden los datos ayudar a una transformación social en favor de las personas y el medioambiente, qué oportunidades de colaboración existen y qué otras están por crearse.

Habla con nosotros/as Mar Cabra, una conocida periodista de investigación y especialista en análisis de datos que ha estado al frente de la Unidad de Datos e Investigación del Consorcio Internacional de Periodistas de Investigación, ganador del premio Pulitzer de 2017 con la investigación conocida como “Los papeles de Panamá”.

Ignacio Jovtis es el Responsable de Investigación y Políticas de Amnistía Internacional en España. AI usa testimonios, cartografía digital datos y fotografía satelitales para denunciar y producir evidencias de abusos de los derechos humanos en la guerra en Siria, de la apropiación militar de tierras en pueblos rohingyas y sobre la crisis de refugiados en el Mediterráneo.

También nos acompaña Juan Carlos Alonso, Diseñador de Vizzuality, una organización creada para hacer del diseño de datos un impulsor del cambio. Vizzuality ofrece aplicaciones que ayudan a la mejor comprensión de los datos a través de su visualización para comprender procesos como la deforestación, la preparación para los desastres, el flujo mundial del comercio de productos agrícolas o la acción contra el cambio climático en todo el mundo.

Juanlu Sánchez es otro conocido periodista. Cofundador y subdirector de eldiario.es, está especializado en contenidos digitales, nuevos medios y fórmulas de sostenibilidad para el periodismo independiente como el modelo de socios de eldiario.es. Ha dirigido y colaborado en diversas investigaciones basadas en datos, como por ejemplo la de las tarjetas black de Bankia.

Adolfo Antón es el Responsable del DataLab del Medialab-Prado, desde donde ha dirigido la experimentación, producción y divulgación de proyectos en torno a la cultura de los datos y el fomento de los datos abiertos. Adolfo ha sido representante del Open Knowledge Foundation España, una organización dedicada a financiar y fomentar los proyectos de datos, entre otros.

Modera Miren Gutiérrez, directora del Programa de postgrado “Análisis, investigación y comunicación de datos” e investigadora de la Universidad de Deusto. Miren está por publicar un libro titulado Data activism and social change, precisamente sobre los datos y la transformación social. La conferencia será recogida en imágenes y compartida por el reconocido facilitador gráfico Jorge Martin, quien tomará nota de las propuestas e ideas planteadas por los/as panelistas y participantes.

Tanto si quieres saber qué se está haciendo con los datos para mejorar el mundo como si quieres imaginar qué puedes hacer tú, te invitamos a participar en este debate que no pretende ser una conferencia al uso, sino un diálogo interactivo, abierto, dinámico y participativo entre todos/as los/as presentes.

Entrada libre hasta completar aforo.

[blog] Tech, data and social change: A plea for cross-disciplinary engagement, historical memory, and … Critical Community Studies

Kersti R. Wissenbach | March 2018

It has been a while since I first got my feet into the universe of technology and socio-political change. Back then, coming from a critical development studies and communication science background, I was fascinated by the role community radio could play in fostering dialogue among communities in remote areas, and between those communities and their government representatives.

My journey started in the early 2000s, in the most remote parts of Upper West Ghana, with Radio Progress, a small community radio station doing a great job in embracing diversity. Single feature mobile phones were about to become a thing in the country and the radio started to experiment with call-in programs for engaging its citizens in live discussions with local politicians. Before, radio volunteers would drive to the different villages in order to collect people’s concerns, and only then bring those recorded voices back into a studio-based discussion with invited politicians. The community could merely listen in as their concerns were discussed. With the advent of mobile phones, people suddenly could do more than just passively listen to the responses: finally they could engage in real-time dialogue with their representatives, hearing their own voices on air. Typically, people were gathering with family and other community members during the call-in hours to voice their concerns collectively. Communities would not only raise concerns, but also share positive experiences with local representatives following up on their requests. These stories encouraged neighbouring communities to also get involved in the call-in programs to raise their concerns and needs to be addressed.

Fast forward to today and much has changed on the ‘tech for social change’ horizon, at least if we listen to donor agendas and the dominant discourses in the field and in the academia. But what has really changed is largely one thing: the state of technology [1]. In the space of two decades, our enthusiasm, and donor attention, fixed on the ubiquity of mobile technologies, followed by online (crowdsourcing) platforms, social media, everything data (oh, wait … BIG data), and blockchain technology.

Whilst much of what has changed in these regards over the last few decades can be bundled under the Information and Communication for Development (ICT4D) label, one aspect seems to remain constant: change, if it is meant to happen and last, has to be rooted in the contexts and needs of those it intends to address. This is the ultimate ingredient for direct and inclusive engagement of the so-called civil society. Like a cake that needs yeast to rise, no matter whether we add chocolate or lemon, socio-political change in the interest of the people requires the buy-in of the people, no matter what tech is on the menu at a certain moment in time, and in a certain place of the world.

We have learnt many lessons along the way, and we had to sometimes learn them the hard way. Some are condensed in initiatives such as the Principles for Digital Development, a living set of principles helping practitioners engaging with the role of technologies in social or political change programs to learn from past experiences, in order to avoid falling into the same traps – be it of technological, political, and/or ethical nature.

We have observed an upsurge in ‘civic’ users of technologies for facilitating people’s direct engagement in governance, coupled with an emphasis on ‘open government models’. Much of this work emerged in parallel to or from earlier ICT4D experiences, and largely taps into the same funding structures. The lessons learned should be a shared heritage in the field. With various early programs coming to an end, this transnational community of well-intended practitioners, many of which have been involved in what we have earlier called ICT4D work, is now reflecting on the effectiveness of technology in promoting civil society participation in governance dynamics. What puzzles me year after year, however, is how practitioners of civic tech and open government, currently producing ‘first lessons learned’ on the effectiveness of technology in civil society participation in governance, are largely reproducing what we already know, and thus lessons we should have learnt. As critical as I am towards project work driven by traditional development cooperation, all this leaves me wondering what is novel, if anything, in these newest networks – largely breathing from the same funding pots.

New developments in the tech field do not liberate us from the responsibility to learn from what has already been learned – and build on it. The lessons learnt in decades of development communication and ICT4D works evidently cut across technological innovations, and apply to mobile technology as much as to the blockchain. Most importantly: different socio-political contexts call for personalized solutions, given the challenges remain distinct and increase in complexity, as we can see in the growing literature on critical data studies (see e.g. Dalton et al., 2016; Kitchin and Lauriault, 2014).

The critical role of proactive communities, their contexts and needs in fostering social or political change has been discussed since decades. Besides, as the Radio Progress anecdote shows, it applies across technologies. Sadly, once again, the dominant civic tech discourse seems to keep departing from the ‘tech’ rather than the ‘civic’. Analyses start off from the technology-in-governance side, rather than from the much-needed critical discourse of the fundamental role of power in governance: how it is constructed, reproduced, and distributed.

Departing from the aseptic end of the spectrum confines us to a tech-centric perspective, with all the limitations highlighted since the early days of Communication for Social Change and ICT4D critique. Instead, we should reflect on how power structures are seeded and nourished from within the very same communities. This relates to issues such as geographical as much as skill-related biases, originating patterns of exclusion that no technology alone can solve. Those biases are then reproduced, not solved, by technological solutions which aim would be, instead, to enable inclusive forms of governance.

For the civic tech field to move forward, we should move beyond an emphasis on feedback allocation and end-users ultimately centring on the technological component; we should instead adopt a broader perspective in which we recognise the user not merely as a tech consumer/adopter, but as a complex being embedded in civil society networks and power structures. We, therefore, should ask critical questions beyond technology and about communities instead; we should ask ourselves, for example, how to best integrate people’s needs and backgrounds across all stages of civic tech programs. Such a perspective should include a critical examination of who the driving forces of the civic tech community are and how they do subsequently affect decision-making on the development of infrastructures. What is crucial to understand, I argue, is that only inclusive communities can really translate inclusive technology approaches and, consequently, inclusive governance.

From the perspective of an academic observer, a disciplinary evolution is in order too, if we are to capture, understand, and critically contribute to these dynamics. The proposed shift of focus from the ‘tech’ to the ‘civic’ should be mirrored in the literature with a new sub-field, which we may call Critical Community Studies. Emerging at the crossroad of disciplines such as Social Movement Studies, Communication for Social Change, and Critical Data Studies, Critical Community Studies would encourage to taking the community as an entry point in the study of technology for social change. This means, in a case such as the civic tech community, addressing issues such as internal diversity, inclusiveness of decision-making processes, etc. and ways of different ways of engaging people. It also relates to the roots of decisions made in civic tech projects, and in how far those communities, supposed to benefit from certain decisions, have a seat on the table. More generally, Critical Community Studies should invite to critically reflect on the concept of inclusion, both for practitioner agendas and academic frameworks. It would also encourage us to contextualize, take a step back and ask difficult questions, departing from critical development and communication studies (see e.g. Enghel, 2014; Freire, 1968; Rodriguez, 2016) , while taking a feminist perspective (see e.g. Haraway, 1988; Mol, 1999).

Since such a disciplinary evolution cannot but happen in dialogue with existing approaches and thinkers, I would wish to see this post to evolve into a vibrant, cross-disciplinary conversation on how a Critical Community Studies could look like.

 

I would like to thank Stefania Milan for very valuable and in-depth feedback and insights whilst writing this post.

 

 

Cited work

Dalton CM, Taylor L and Thatcher (alphabetical) J (2016) Critical Data Studies: A dialog on data and space. Big Data & Society 3(1): 2053951716648346. DOI: 10.1177/2053951716648346.

Enghel F (2014) Communication, Development, and Social Change: Future Alternatives. In: Global communication: new agendas in communication. Routledge, pp. 129–141.

Freire P (1968) Pedagogy of the Oppressed. New York: Herder and Herder.

Haraway D (1988) Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective. Feminist Studies 14(3): 575–599. DOI: 10.2307/3178066.

Kitchin R and Lauriault T (2014) Towards Critical Data Studies: Charting and Unpacking Data Assemblages and Their Work. ID 2474112, SSRN Scholarly Paper. Rochester, NY: Social Science Research Network. Available at: https://papers.ssrn.com/abstract=2474112 (accessed 19 March 2018).

Mol A (1999) Ontological politics. A word and some questions. The Sociological Review 47(S1): 74–89. DOI: 10.1111/j.1467-954X.1999.tb03483.x.

Rodriguez C (2016) Human agency and media praxis: Re-centring alternative and community media research. Journal of Alternative and Community Media 1(0): 36–38.

 

1 I am consciously not using the innovation term here since I truly believe that innovation can only be what truly features into people’s contexts and needs. Innovation, then, is not to be confused with the latest tech advancement or hype.

[blog] Facebook newsfeed changes: Three hypotheses to look into the future

Image: Vincenzo Cosenza

In this blog post, DATACTIVE research associate Antonio Martella is looking forward to the consequences of Facebook’s news feed modifications as result of larger corporate policy changes. He investigates and discusses implications through three hypotheses: 1) the divide between the attention-rich and the attention poor will grow 2) increasing engagement with peer-created content will tighten the filter bubble aspect of networking and 3) the “new” news feed will have a negative impact on users’ mood.

Guest Author: Antonio Martella

On November 11th, 2017, Facebook has announced that the user timeline will change in January 2018. In their words:

“With this update, we will also prioritize posts that spark conversations and meaningful interactions between people. To do this, we will predict which posts you might want to interact with your friends about and show these posts higher in the feed. These are posts that inspire back-and-forth discussion in the comments and posts that you might want to share and react to – whether that’s a post from a friend seeking advice, a friend asking for recommendations for a trip, or a news article or video prompting lots of discussions. […] We will also prioritize posts from friends and family over public content, consistent with our News Feed values.” (Newsroom Facebook 2018)

Any modification in the feed algorithm will have many consequences, and these are not equally predictable. Facebook is a very complicated environment, semi-public in nature and not only related to friendship management. In fact, as the Pew Research Center reported last September, 67% of Americans consume news over social media. This pattern seems to apply to the European news consumption too, where youngsters are exposed to news mostly in a social media context rather than television or newspaper. Indeed, as the Reuters Institute’s Digital News Report 2017 shows, many users follow others because of the news they share.

According to the Pew Research Report, Facebook surpasses other social media as a source of news consumption. This is partially due to the large userbase Facebook has, and partially because news is actually interwoven with people’s timelines. The Digital News Report also shows that exposure to news in Facebook is often incidental; a direct result of news shared by other users, a wide range of news companies that are followed, etc. Notwithstanding, we need to keep in mind that exposure to any content in social media or search engines is algorithm-driven.

Following these considerations, there are several possible consequences to the Facebook news feed changes. This blogpost invests into three probable implication, being

  1. the divide between the attention-rich and the attention poor will grow;
  2. continuous personalisation;
  3. negative impact on users’ mood

1. The divide between the attention-rich and the attention poor will grow

All pages and groups that share content on Facebook will lose visibility and revenues that come from users reading their posts, clicking their links, and visiting their websites1. It’s easy to guess that those who want to remain visible have two choices: either pay more for Facebook ads in order to make their posts visible; or create more engaging content. But the generated engagement in Facebook is deeply connected with the number of followers. This will probably increase the gap between attention reach and attention poor, which is in line with the observed Matthew effect (Merton, 1968) that rules many patterns and practices online (Barabasi, 2013) and in social media.

In fact, many aspects of the society both online and offline are governed by the preferential attachment process that stays behind the so-called “Matthew effect” or the “80/20 rule”. Hence, the more connection you have the more visible you are, and the more new connections you would get as a consequence. This principle can easily be illustrated by the fact that famous websites and people tend to have more followers on social media. But the other way around is equally true: the fewer connection you have, the less attention you would get. In conclusion, contents produced by people or organizations with less power/resources and with lower budgets will decrease in visibility.

2. Continuous personalisation

The second consequence of the news feed change deals with the kind of content that will be dominant in users’ feeds. According to Mark Zuckerberg, content produced and shared by “friends and family” will be more visible in all Facebook timelines. But a news feed dominated by friends’ posts could arguably exacerbate two negative social media aspects, previously expressed through notions of the filter bubbles and the echo chamber. Online social networks developed in social media platforms are strongly based on homophily (Barberà, 2014; Aiello et al 2012) meaning that users connect with others who share similar interests, values, political views, etc. This typical behaviour is also found in offline social networks (McPherson, Smith-Lovin, Cook, 2001), and shows its most problematic characteristics when focusing on information diffusion.

On the one hand, this change will foster the filter bubble in which we are all involved. In fact, filter bubbles (Pariser, 2011) are the result of users’ activities on the web: social media algorithms which continuously learn from every users’ clicks and likes2. On the other hand, more homophily in social media due to the prevalence of “friends and family contents” could easily sustain the echo chamber effect. This phenomenon preceded social media platforms, for like-minded people love to talk to each other fostering their opinions and biases. However, in social media, it is easier to avoid a contrasting point of views, values, or interests as a consequence of the self-selection of “friends”, pages, and groups. Indeed, as research has highlighted, there is a user tendency to promote their favourite narratives and to form polarised groups on Facebook (Quattrociocchi, Scala, Sunstein 2016; Bakshy, Messing, Adamic, 2015) even though it is not a clear and deterministic process (Barberà et al. 2015).

Based on these last considerations, another outcome of news feed changes will be a growth in the visibility of friends’ opinions and points of view. This will most probably result in more polarised information flow in users’ news feeds and a limited number of different point of views and professional (or semi-professional) content. In practice this means that if we would think about a contested news like glyphosate and cancer causation, we have to take in account that information sources will be more socially driven; the chance to read a different point of views and professional news will be smaller than before.

3. Negative impact on users’ mood

The news feed changes will probably influence the mood of billions of people in an inscrutable way. One can say that a news feed more populated by friend’s content would have a negative impact on happiness. According to Mark Zuckerberg “the research shows that when we use social media to connect with people we care about, it can be good for our well-being”. In fact, according to an experiment conducted on users timeline (Kramer, Guillory, Hancock, 2013) content on the users’ timeline does indeed influences their mood. As many researchers have shown, personal feelings (happiness, depression, etc.) flow through offline social networks (Fowler, Christakis, 2008) and their representation in online environments seems to share similar diffusion patterns. In other words: moods contagiously spread online. And in extension, recent scholarly and non-scholarly work shows that scrolling through your Facebook feed can have a negative impact on well-being (Shakya, Christakis, 2017)3. Lastly, it has been demonstrated that the constant bombardment of everyone’s news, biases the attempt to provide the best representation of the self and it seems to have a negative impact on happiness.

Questions to ask

Throughout the hypothesis, I have tried to show some real-life aspects that might be affected by the important changes on Facebook algorithms. As Facebook stated, there are around 2 billion active users on its platform monthly.

These statements subsequently evoke two questions:

  1. Can these changes be made by a private company without any form of public discussion?
  2. Is it our democratic right to scrutinize algorithms as organiser of public space?

Further information on how Facebook algorithms work can be found here: an interesting article edited by Share Lab that has tried to shed some light on what is behind this platform.

 

References

Aiello, Luca Maria, Barrat, Alain, Schifanella, Rossano, Cattuto, Ciro, Markines, Benjamin, Menczer, Filippo. 2012. Friendship prediction and homophily in social media. ACM Trans. Web 6, 2, Article 9, 33 p. 66.

Bakshy, Eytan, Messing, Solomon, Adamic, Lada A. 2015.Exposure to ideologically diverse news and opinion on Facebook in Science 05 Jun 2015: Vol. 348, Issue 6239, pp. 1130-1132.

Pariser, Eli, 2012, The Filter Bubble: What The Internet Is Hiding From You, Penguin: London.

Quattrociocchi, Walter, Scala, Antonio, Sunstein, Cass R. 2013. Echo Chambers on Facebook. Available at SSRN: https://ssrn.com/abstract=2795110.

Shakya, Holly B., Christakis, Nicholas A. 2017. Association of Facebook Use With Compromised Well-Being: A Longitudinal Study in American Journal of Epidemiology, 185:3, pp. 203–211.

Rogers, Richard, 2015. Digital Methods for Web Research, in Emerging Trends in the Social and Behavioral Sciences: An Interdisciplinary, Searchable, and Linkable Resource (ed. Scott, Roberts; Buchmann, Marlis C.; Kosslyn Stephan), Wiley & Sons: New York

 

  1. For example, this is exactly what happened to the blog LittleThings. This blog had to shut down a month after the news feed change due to the web traffic drop.
  2. This is already happening as an Italian experiment on Facebook have partially shown during the last Italian election (link, unfortunately only in Italian). According to this experiment, Facebook news feed shows different kind of content and media (photo, video, web links) based on likes, comment and shares of each user. Indeed, according to Facebook statements, proposed content will be more based on each user’s intention to interact (algorithmically predicted) fostering the visibility of tailored content.
  3. For example «Liking others’ content and clicking links posted by friends were consistently related to compromised well-being, whereas the number of status updates was related to reports of diminished mental health» (Shakya, Christakis, 2017, p. 210).

 

On the author: Antonio is a PhD candidate in Political Science at the University of Pisa. His research focus is political leaders populism in social media. His approach coincides with the Digital Methods for Web Research recommendations (Rogers, 2015), and he is particularly interested in social media algorithms and their effects.