social media

How can we study disguised propaganda on social media? Some methodological reflections

Curated on May 29, 2017August 3, 2018 by Stefaan Verhulst

Jannick Schou and Johan Farkas at DataDrivenJournalism: ’Fake news’ has recently become a seemingly ubiquitous concept among journalists, researchers, and citizens alike. With the rise of platforms such as Facebook and Twitter, it has become possible to spread deliberate forms of misinformation in hitherto unforeseen ways. This has also spilled over into the political domain, where new forms of (disguised) propaganda and false information have recently begun to emerge. These new forms of propaganda have very real effects: they serve to obstruct political decision-making processes, instil false narratives within the general public, and add fuel to already heated sites of political conflict. They represent a genuine democratic problem.

Yet, so far, both critical researchers and journalists have faced a number of issues and challenges when attempting to understand these new forms of political propaganda. Simply put: when it comes to disguised propaganda and social media, we know very little about the actual mechanisms through which such content is produced, disseminated, and negotiated. One of the key explanations for this might be that fake profiles and disguised political agendas are incredibly difficult to study. They present a serious methodological challenge. This is not only due to their highly ephemeral nature, with Facebook pages being able to vanish after only a few days or hours, but also because of the anonymity of its producers. Often, we simply do not know who is disseminating what and with what purpose. This makes it difficult for us to understand and research exactly what is going on.

This post takes its point of departure from a new article published in the international academic journal New Media & Society. Based on the research done for this article, we want to offer some methodological reflections as to how disguised propaganda might be investigated. How can we research fake and disguised political agendas? And what methodological tools do we have at our disposal?…

two main methodological advices spring to mind. First of all: collect as much data as you can in as many ways as possible. Make screenshots, take detailed written observations, use data scraping, and (if possible) participate in citizen groups. One of the most valuable resources we had at our disposal was the set of heterogeneous data we collected from each page. Using this allowed us to carefully dissect and retrace the complex set of practices involved in each page long after they were gone. While we certainly tried to be as systematic in our data collection as possible, we also had to use every tool at our disposal. And we had to constantly be on our toes. As soon as a page emerged, we were there: ready to write down notes and collect data.

Second: be willing to participate and collaborate. Our research showcases the immense potential in researchers (and journalists) actively collaborating with citizen groups and grassroots movements. Using the collective insights and attention of this group allowed us to quickly find and track down pages. It gave us renewed methodological strength. Collaborating across otherwise closed boundaries between research and journalism opens up new avenues for deeper and more detailed insights….(More)”

Data Collaboratives: exchanging data to create public value across Latin America and the Caribbean

Curated on May 26, 2017July 19, 2019 by Stefaan Verhulst

Stefaan Verhulst, Andrew Young and Prianka Srinivasan at IADB’s Abierto al Publico: “Data is playing an ever-increasing role in bolstering businesses across Latin America – and the rest of the word. In Brazil, Mexico and Colombia alone, the revenue from Big Data is calculated at more than US$603.7 million, a market that is only set to increase as more companies across Latin America and the Caribbean embrace data-driven strategies to enhance their bottom-line. Brazilian banking giant Itau plans to create six data centers across the country, and already uses data collected from consumers online to improve cross-selling techniques and streamline their investments. Data from web-clicks, social media profiles, and telecommunication services is fueling a new generation of entrepreneurs keen to make big dollars from big data.

What if this same data could be used not just to improve business, but to improve the collective well-being of our communities, public spaces, and cities? Analysis of social media data can offer powerful insights to city officials into public trends and movements to better plan infrastructure and policies. Public health officials and humanitarian workers can use mobile phone data to, for instance, map human mobility and better target their interventions. By repurposing the data collected by companies for their business interests, governments, international organizations and NGOs can leverage big data insights for the greater public good.

Key question is thus: How to unlock useful data collected by corporations in a responsible manner and ensure its vast potential does not go to waste?

“Data Collaboratives” are emerging as a possible answer. Data collaboratives are a new type of public-private partnerships aimed at creating public value by exchanging data across sectors.

Research conducted by the GovLab finds that Data Collaboratives offer several potential benefits across a number of sectors, including humanitarian and anti-poverty efforts, urban planning, natural resource stewardship, health, and disaster management. As a greater number of companies in Latin America look to data to spur business interests, our research suggests that some companies are also sharing and collaborating around data to confront some of society’s most pressing problems.

Consider the following Data Collaboratives that seek to enhance…(More)”

Twitter as a data source: An overview of tools for journalists

Curated on May 24, 2017July 19, 2019 by Stefaan Verhulst

Wasim Ahmed at Data Driven Journalism: “Journalists may wish to use data from social media platforms in order to provide greater insight and context to a news story. For example, journalists may wish to examine the contagion of hashtags and whether they are capable of achieving political or social change. Moreover, newsrooms may also wish to tap into social media posts during unfolding crisis events. For example, to find out who tweeted about a crisis event first, and to empirically examine the impact of social media.

Furthermore, Twitter users and accounts such as WikiLeaks may operate outside the constraints of traditional journalism, and therefore it becomes important to have tools and mechanisms in place in order to examine these kinds of influential users. For example, it was found that those who were backing Marine Le Pen on Twitter could have been users who had an affinity to Donald Trump.

There remains a number of different methods for analysing social media data. Take text analytics, for example, which can include using sentiment analysis to place bulk social media posts into categories of a particular feeling, such as positive, negative, or neutral. Or machine learning, which can automatically assign social media posts to a number of different topics.

There are other methods such as social network analysis, which examines online communities and the relationships between them. A number of qualitative methodologies also exist, such as content analysis and thematic analysis, which can be used to manually label social media posts. From a journalistic perspective, network analysis may be of importance initially via tools such as NodeXL. This is because it can quickly provide an overview of influential Twitter users alongside a topic overview.

From an industry standpoint, there has been much focus on gaining insight into users’ personalities, through services such as IBM Watson’s Personality Insights service. This uses linguistic analytics to derive intrinsic personality insights, such as emotions like anxiety, self-consciousness, and depression. This information can then be used by marketers to target certain products; for example, anti-anxiety medication to users who are more anxious…(An overview of tools for 2017).”

Eliminating the Human

Curated on May 24, 2017August 3, 2018 by Stefaan Verhulst

David Byrne: I have a theory that much recent tech development and innovation over the last decade or so has had an unspoken overarching agenda—it has been about facilitating the need for LESS human interaction. It’s not a bug—it’s a feature. We might think Amazon was about selling us books we couldn’t find locally—and it was and what a brilliant idea—but maybe it was also just as much about eliminating human interaction. I see a pattern emerging in the innovative technology that has gotten the most attention, gets the bucks and often, no surprise, ends up getting developed and implemented. What much of this technology seems to have in common is that it removes the need to deal with humans directly. The tech doesn’t claim or acknowledge this as its primary goal, but it seems to often be the consequence. I’m sort of thinking maybe it is the primary goal. There are so many ways imagination can be manifested in the technical sphere. Many are wonderful and seem like social goods, but allow me a little conspiracy mongering here—an awful lot of them have the consequence of lessening human interaction.

I suspect that we almost don’t notice this pattern because it’s hard to imagine what an alternative focus of tech development might be. Most of the news we get barraged with is about algorithms, AI, robots and self driving cars, all of which fit this pattern, though there are indeed many technological innovations underway that have nothing to do with eliminating human interaction from our lives. CRISPR-cas9 in genetics, new films that can efficiently and cheaply cool houses and quantum computing to name a few, but what we read about most and what touches us daily is the trajectory towards less human involvement. Note: I don’t consider chat rooms and product reviews as “human interaction”; they’re mediated and filtered by a screen.

I am not saying these developments are not efficient and convenient; this is not a judgement regarding the services and technology. I am simply noticing a pattern and wondering if that pattern means there are other possible roads we could be going down, and that the way we’re going is not in fact inevitable, but is (possibly unconsciously) chosen.

Here are some examples of tech that allows for less human interaction…

Lastly, “Social” media- social “interaction” that isn’t really social.

While the appearance on social networks is one of connection—as Facebook and others frequently claim—the fact is a lot of social media is a simulation of real social connection. As has been in evidence recently, social media actually increases divisions amongst us by amplifying echo effects and allowing us to live in cognitive bubbles. We are fed what we already like or what our similarly inclined friends like… or more likely now what someone has payed for us to see in an ad that mimics content. In this way, we actually become less connected except to those in our group…..

Many transformative movements in the past succeed based on leaders, agreed upon principles and organization. Although social media is a great tool for rallying people and bypassing government channels, it does not guarantee eventual success.

Social media is not really social—ticking boxes and having followers and getting feeds is NOT being social—it’s a screen simulation of human interaction. Human interaction is much more nuanced and complicated than what happens online. Engineers like things that are quantifiable. Smells, gestures, expression, tone of voice, etc. etc.—in short, all the various ways we communicate are VERY hard to quantify, and those are often how we tell if someone likes us or not….

To repeat what I wrote above—humans are capricious, erratic, emotional, irrational and biased in what sometimes seem like counterproductive ways. I’d argue that though those might seem like liabilities, many of those attributes actually work in our favor. Many of our emotional responses have evolved over millennia, and they are based on the probability that our responses, often prodded by an emotion, will more likely than not offer the best way to deal with a situation….

Our random accidents and odd behaviors are fun—they make life enjoyable. I’m wondering what we’re left with when there are fewer and fewer human interactions. Remove humans from the equation and we are less complete as people or as a society. “We” do not exist as isolated individuals—we as individuals are inhabitants of networks, we are relationships. That is how we prosper and thrive….(More)”.

The cloud, the crowd, and the city: How new data practices reconfigure urban governance?

Curated on May 20, 2017August 3, 2018 by Stefaan Verhulst

Introduction to Special Issue of Big Data & Society by Philip Ashton, Rachel Weber and Matthew Zook: “The urban archetype of the flâneur, so central to the concept of modernity, can now experience the city in ways unimaginable one hundred years ago. Strolling around Paris, the contemporary flâneur might stop to post pictures of her discoveries on Instagram, simultaneously identifying points of interest to the rest of her social network and broadcasting her location (perhaps unknowingly). The café she visits might be in the middle of a fundraising campaign through a crowdfunding site such as Kickstarter, and she might be invited to tweet to her followers in exchange for a discount on her pain au chocolate. As she ambles about Paris, the route of her stroll is captured by movement sensors positioned on top of street lights, and this data—aggregated with that of thousands of other pedestrians—could be used by the City of Paris to sync up transit schedules. And if those schedules were not convenient, she might tap Uber to whisk her home to her threadbare pension booked on AirBnB.

This vignette attests to the transformation of the urban experience through technology-enabled platforms that allow for the quick mobilization and exchange of information, public services, surplus capacity, entrepreneurial energy, and money. However, these changes have implicated more than just consumers, as multiple technologies have been taken up in urban governance processes through platforms variously labeled as Big Data, crowd sourcing, or the sharing economy. These systems combine inexpensive data collection and cloud-based storage, distributed social networks, geotagged locational sensing, mobile access (often through “app” platforms), and new collaborative entrepreneurship models to radically alter how the needs of urban residents are identified and how services are delivered and consumed in so-called “smart cities” (Townsend, 2013). Backed by Big Data, smart city initiatives have made inroads into urban service provision and policy in areas such as e-government and transparency, new forms of public-private partnerships through “urban lab” arrangements, or models such as impact investing, civic hacking, or tactical urbanism (cf. Karvonen and van Heur, 2014; Kitchin, 2014; Swyngedouw, 2005).

In the rhetoric used by their boosters, the vision and practice of these technologies “disrupts” existing markets by harnessing the power of “the crowd”—a process fully evident in sectors such as taxi (Uber/Lyft), hoteling (AirBnB), and finance (peer-to-peer lending). However, the notion of disruption has also targeted government bureaucracies and public services, with new initiatives seeking to insert crowd mechanisms or characteristics—at once self-organizing and collectively rational (Brabham, 2008)—into public policy. These mechanisms envision reconfiguring the traditional relationship of public powers with planning and governance by vesting data collection and problem-solving in crowd-like institutional arrangements that are partially or wholly outside the purview of government agencies. While scholars are used to talking about “governance beyond-the-state” (Swyngedouw, 2005) in terms of privatization and a growing scope for civil society organizations, technological intermediation potentially changes the scale and techniques of governance as well as its relationship to sovereign authority.

For instance, civic crowdfunding models have emerged as new means of organizing public service provision and funding community economic development by embracing both market-like bidding mechanisms and social-network technologies to distribute responsibility for planning and financing socially desirable investments to laypeople (Brickstarter, 2012; Correia de Freitas and Amado, 2013; Langley and Leyshon, 2016). Other practices are even more radical in their scope. Toronto’s Urban Repair Squad—an offshoot of the aptly named Critical Mass bike happenings—urges residents to take transportation planning into their own hands and paint their own bike lanes. Their motto: “They say city is broke. We fix. No charge.” (All that is missing is the snarky “you’re welcome” at the end.)

Combined, these emerging platforms and practices are challenging the tactics, capabilities, and authorizations employed to define and govern urban problems. This special theme of Big Data & Society picks up these issues, interrogating the emergence of digital platforms and smart city initiatives that rely on both the crowd and the cloud (new on-demand, internet-based technologies that store and process data) to generate and fold Big Data into urban governance. The papers contained herein were presented as part of a one-day symposium held at the University of Illinois at Chicago (UIC) in April 2015 and sponsored by UIC’s Department of Urban Planning and Policy. Setting aside the tired narratives of individual genius and unstoppable technological progress, workshop participants sought to understand why these practices and platforms have recently gained popularity and what their implementation might mean for cities. Papers addressed numerous questions: How have institutional supports and political-economic contexts facilitated the ascendance of “crowd” and “cloud” models within different spheres of urban governance? How do their advocates position them relative to imaginaries of state or market failure/dysfunction? What kinds of assumptions and expectations are embedded in the design and operation of these platforms and practices? What kinds of institutional reconfigurations have been spurred by the push to adopt smart city initiatives? How is information collected through these initiatives being used to advance particular policy agendas? Who is likely to benefit from them?…(More)”.

What next for digital social innovation? Realising the potential of people and technology to tackle social challenges

Curated on May 17, 2017August 3, 2018 by Stefaan Verhulst

Matt Stokes et al at nesta: “This report, and accompanying guide, produced as part of the DSI4EU project, maps the projects and organisations using technology to tackle social challenges across Europe, and explores the barriers to the growth of digital social innovation.

Key findings

There are almost 2,000 organisations and over 1,000 projects involved in digital social innovation (DSI) across Europe, with the highest concentration of activity in Western and Southern Europe.
Despite this activity, there are relatively few examples of DSI initiatives delivering impact at scale. The growth of DSI is being held back by barriers at the system level and at the level of individual projects.
Projects and organisations involved in DSI are still relatively poorly connected to each other. There is a pressing need to grow strong networks within and across countries and regions to boost collaboration and knowledge-sharing.
The growth of DSI is being held back by lack of funding and investment across the continent, especially outside Western Europe, and structural digital skills shortages.
Civil society organisations and the public sector have been slow to adopt DSI, despite the opportunity it offers them to deliver better services at a lower cost, although there are emerging examples of good practice from across Europe.
Practitioners struggle to engage citizens and users, understand and measure the impact of their digital social innovations, and plan for growth and sustainability.

Across Europe, thousands of people, projects and organisations are using digital technologies to tackle social challenges in fields like healthcare, education, employment, democratic participation, migration and the environment. We call this phenomenon digital social innovation.

Through crowdmapping DSI across Europe, we find that there are almost 2,000 organisations and over 1,000 projects using open and collaborative technologies to tackle social challenges. We complement this analysis by piloting experimental data methods such as Twitter analysis to understand in further depth the distribution of DSI across Europe. You can explore the data on projects and organisations on digitalsocial.eu.

However, despite widespread activity, few initiatives have grown to deliver impact at scale, to be institutionalised, or to become “the new normal”.

In this research, we find that weak networks between stakeholders, insufficient funding and investment, skills shortages, and slow adoption by public sector and established civil society organisations is holding back the growth of DSI…(More)”.

Tech Companies Should Speak Up for Refugees, Not Only High-Skilled Immigrants

Curated on May 17, 2017August 3, 2018 by Stefaan Verhulst

Mark Latonero at Harvard Business Review: “The Trump administration’s latest travel ban is back in U.S. federal court. The Fourth Circuit, based in Virginia, and Ninth Circuit, based in San Francisco, are hearing cases challenging the latest executive order banning immigrants and refugees from six Muslim majority countries from entering the United States. Joining the fray are 162 technology companies, whose lawyers collectively filed an amicus brief to both courts. Amazon, eBay, Google, Facebook, Netflix, and Uber are among the companies urging federal judges to rule against the executive order, detailing why it is unjust and how it would hurt their businesses.

While the 40-page brief is filled with arguments in support of immigration, it hardly speaks about refugees, except to note that those seeking protection should be welcomed. Any multinational company with a diverse workforce would be concerned about limits to international hiring and employee travel. But tech companies should also be concerned about the refugee populations that depend on their digital services for safety and survival.

In researching migration and the refugee crisis in Europe, my team and I interviewed over 140 refugees from Syria, and I’ve learned that technology has been crucial to those fleeing war and violence across the Middle East and North Africa. Services like Google Maps, Facebook, WhatsApp, Skype, and Western Union have helped refugees find missing loved ones or locate safe places to sleep. Mobile phones have been essential — refugees have even used them on sinking boats to call rescue officials patrolling the Mediterranean.

Refugees’ reliance on these platforms demonstrates what tech companies often profess: that innovation can empower people to improve their lives and society. Tech companies did not intend for their tools to facilitate one of the largest mass movements of refugees in history, but they have a responsibility to look out for the safety and security of the vulnerable consumers using their products.

Some tech companies have intervened directly in the refugee crisis. Google has created apps to help refugees in Greece find medical facilities and other services; Facebook promised to provide free Wi-Fi in U.N. refugee camps. A day after President Trump issued the first travel ban, which initially suspended the U.S. Refugee Admissions Program, Airbnb announced it would provide free housing to refugees left stranded….

The sector should extend these efforts by making sure its technologies aren’t used to target broad groups of people based on nationality or religion. Already the U.S. Customs and Border Protection (CPB) is asking for the social media accounts — even passwords — of visitors from other counties. The Council on American-Islamic Relations has filed complaints against the CPB, stating that Muslim American citizens have been subjected to enhanced screening that includes scrutiny of their social media accounts and cell phones.

Trump has talked about creating a database to identify and register Muslims in America, including refugees. A number of companies, including IBM, Microsoft, and Salesforce, have stated they will not help build a Muslim registry if asked by the government. In addition, a group of nearly 3,000 American tech employees signed an online pledge promising they would not develop data processing systems to help the U.S. government target individuals based on race, religion, or national origin….(More)”.