Social media big data analytics: A survey


Norjihan Abdul Ghani et al in Computers in Human Behavior: “Big data analytics has recently emerged as an important research area due to the popularity of the Internet and the advent of the Web 2.0 technologies. Moreover, the proliferation and adoption of social media applications have provided extensive opportunities and challenges for researchers and practitioners. The massive amount of data generated by users using social media platforms is the result of the integration of their background details and daily activities.

This enormous volume of generated data known as “big data” has been intensively researched recently. A review of the recent works is presented to obtain a broad perspective of the social media big data analytics research topic. We classify the literature based on important aspects. This study also compares possible big data analytics techniques and their quality attributes. Moreover, we provide a discussion on the applications of social media big data analytics by highlighting the state-of-the-art techniques, methods, and the quality attributes of various studies. Open research challenges in big data analytics are described as well….(More)”.

How Social Media Came To The Rescue After Kerala’s Floods


Kamala Thiagarajan at NPR: Devastating rainfall followed by treacherous landslides have killed 210 people since August 8 and displaced over a million in the southern Indian state of Kerala. India’s National Disaster Relief Force launched its biggest ever rescue operation in the state, evacuating over 10,000 people. The Indian army and the navy were deployed as well.

But they had some unexpected assistance.

Thousands of Indian citizens used mobile phone technology and social media platforms to mobilize relief efforts….

In many other cases, it was ordinary folk who harnessed social media and their own resources to play a role in relief and rescue efforts.

As the scope of the disaster became clear, the state government of Kerala reached out to software engineers from around the world. They joined hands with the state-government-run Information Technology Cell, coming together on Slack, a communications platform, to create the website www.keralarescue.in

The website allowed volunteers who were helping with disaster relief in Kerala’s many flood-affected districts to share the needs of stranded people so that authorities could act.

Johann Binny Kuruvilla, a travel blogger, was one of many volunteers. He put in 14-hour shifts at the District Emergency Operations Center in Ernakulam, Kochi.

The first thing he did, he says, was to harness the power of Whatsapp, a critical platform for dispensing information in India. He joined five key Whatsapp groups with hundreds of members who were coordinating rescue and relief efforts. He sent them his number and mentioned that he would be in a position to communicate with a network of police, army and navy personnel. Soon he was receiving an average of 300 distress calls a day from people marooned at home and faced with medical emergencies.

No one trained volunteers like Kuruvilla. “We improvised and devised our own systems to store data,” he says. He documented the information he received on Excel spreadsheets before passing them on to authorities.

He was also the contact point for INSPIRE, a fraternity of mechanical engineering students at a government-run engineering college at Barton Hill in Kerala. The students told him they had made nearly 300 power banks for charging phones, using four 1.5 volt batteries and cables, and, he says, “asked us if we could help them airdrop it to those stranded in flood-affected areas.” A power bank could boost a mobile phone’s charge by 20 percent in minutes, which could be critical for people without access to electricity. Authorities agreed to distribute the power banks, wrapping them in bubble wrap and airdropping them to areas where people were marooned.

Some people took to social media to create awareness of the aftereffects of the flooding.

Anand Appukuttan, 38, is a communications designer. Working as a consultant he currently lives in Chennai, 500 miles by road from Kerala, and designs infographics, mobile apps and software for tech companies. Appukuttan was born and brought up in Kottayam, a city in South West Kerala. When he heard of the devastation caused by the floods, he longed to help. A group of experts on disaster management reached out to him over Facebook on August 18, asking if he would share his time and expertise in creating flyers for awareness; he immediately agreed….(More)”.

Technology is threatening our democracy. How do we save it?


MIT Technology Review: “Our newest issue is live today, in which we dive into the many ways that technology is changing politics.

A major shift: In 2013 we emblazoned our cover with the words, “Big Data Will Save Politics.” When we chose that headline, Barack Obama had just won reelection with the help of a crack team of data scientists. The Arab Spring had already cooled into an Arab Winter, but the social-media platforms that had powered the uprisings were still basking in the afterglow. As our editor in chief Gideon Lichfield writes, today, with Cambridge Analytica, fake news, election hacking, and the shrill cacophony that dominates social media, technology feels as likely to destroy politics as to save it.

The political impact: From striking data visualizations that take a close look at the famed “filter bubble” effect that’s blamed for political polarization to an examination of how big data is disrupting the cozy world of political lobbying, we’re analyzing how emerging technologies are shaping the political landscape, eroding trust, and, possibly, becoming a part of the solution….(More)”.

Data Publics: Urban Protest, Analytics and the Courts


Article by Anthony McCosker and Timothy Graham in MC Journal: “There are many examples globally of the use of social media to engage publics in battles over urban development or similar issues (e.g. Fredericks and Foth). Some have asked how social media might be better used by neighborhood organisations to mobilise protest and save historic buildings, cultural landmarks or urban sites (Johnson and Halegoua). And we can only note here the wealth of research literature on social movements, protest and social media. To emphasise Gerbaudo’s point, drawing on Mattoni, we “need to account for how exactly the use of these media reshapes the ‘repertoire of communication’ of contemporary movements and affects the experience of participants” (2). For us, this also means better understanding the role that social data plays in both aiding and reshaping urban protest or arming third sector groups with evidence useful in social institutions such as the courts.

New modes of digital engagement enable forms of distributed digital citizenship, which Meikle sees as the creative political relationships that form through exercising rights and responsibilities. Associated with these practices is the transition from sanctioned, simple discursive forms of social protest in petitions, to new indicators of social engagement in more nuanced social media data and the more interactive forms of online petition platforms like change.org or GetUp (Halpin et al.). These technical forms code publics in specific ways that have implications for contemporary protest action. That is, they provide the operational systems and instructions that shape social actions and relationships for protest purposes (McCosker and Milne).

All protest and social movements are underwritten by explicit or implicit concepts of participatory publics as these are shaped, enhanced, or threatened by communication technologies. But participatory protest publics are uneven, and as Kelty asks: “What about all the people who are neither protesters nor Twitter users? In the broadest possible sense this ‘General Public’ cannot be said to exist as an actual entity, but only as a kind of virtual entity” (27). Kelty is pointing to the porous boundary between a general public and an organised public, or formal enterprise, as a reminder that we cannot take for granted representations of a public, or the public as a given, in relation to Like or follower data for instance.

If carefully gauged, the concept of data publics can be useful. To start with, the notions of publics and publicness are notoriously slippery. Baym and boyd explore the differences between these two terms, and the way social media reconfigures what “public” is. Does a Comment or a Like on a Facebook Page connect an individual sufficiently to an issues-public? As far back as the 1930s, John Dewey was seeking a pragmatic approach to similar questions regarding human association and the pluralistic space of “the public”. For Dewey, “the machine age has so enormously expanded, multiplied, intensified and complicated the scope of the indirect consequences [of human association] that the resultant public cannot identify itself” (157). To what extent, then, can we use data to constitute a public in relation to social protest in the age of data analytics?

There are numerous well formulated approaches to studying publics in relation to social media and social networks. Social network analysis (SNA) determines publics, or communities, through links, ties and clustering, by measuring and mapping those connections and to an extent assuming that they constitute some form of sociality. Networked publics (Ito, 6) are understood as an outcome of social media platforms and practices in the use of new digital media authoring and distribution tools or platforms and the particular actions, relationships or modes of communication they afford, to use James Gibson’s sense of that term. “Publics can be reactors, (re)makers and (re)distributors, engaging in shared culture and knowledge through discourse and social exchange as well as through acts of media reception” (Ito 6). Hashtags, for example, facilitate connectivity and visibility and aid in the formation and “coordination of ad hoc issue publics” (Bruns and Burgess 3). Gray et al., following Ruppert, argue that “data publics are constituted by dynamic, heterogeneous arrangements of actors mobilised around data infrastructures, sometimes figuring as part of them, sometimes emerging as their effect”. The individuals of data publics are neither subjugated by the logics and metrics of digital platforms and data structures, nor simply sovereign agents empowered by the expressive potential of aggregated data (Gray et al.).

Data publics are more than just aggregates of individual data points or connections. They are inherently unstable, dynamic (despite static analysis and visualisations), or vibrant, and ephemeral. We emphasise three key elements of active data publics. First, to be more than an aggregate of individual items, a data public needs to be consequential (in Dewey’s sense of issues or problem-oriented). Second, sufficient connection is visible over time. Third, affective or emotional activity is apparent in relation to events that lend coherence to the public and its prevailing sentiment. To these, we add critical attention to the affordising processes – or the deliberate and incidental effects of datafication and analysis, in the capacities for data collection and processing in order to produce particular analytical outcomes, and the data literacies these require. We return to the latter after elaborating on the Save the Palace case….(More)”.

Data Colonialism: Rethinking Big Data’s Relation to the Contemporary Subject


Nick Couldry and Ulises Mejias in Television & New Media (TVNM): “...Data colonialism combines the predatory extractive practices of historical colonialism with the abstract quantification methods of computing. Understanding Big Data from the Global South means understanding capitalism’s current dependence on this new type of appropriation that works at every point in space where people or things are attached to today’s infrastructures of connection. The scale of this transformation means that it is premature to map the forms of capitalism that will emerge from it on a global scale. Just as historical colonialism over the long-run provided the essential preconditions for the emergence of industrial capitalism, so over time, we can expect that data colonialism will provide the preconditions for a new stage of capitalism that as yet we can barely imagine, but for which the appropriation of human life through data will be central.

Right now, the priority is not to speculate about that eventual stage of capitalism, but to resist the data colonialism that is under way. This is how we understand Big Data from the South. Through what we call ‘data relations’ (new types of human relations which enable the extraction of data for commodification), social life all over the globe becomes an ‘open’ resource for extraction that is somehow ‘just there’ for capital. These global flows of data are as expansive as historic colonialism’s appropriation of land, resources, and bodies, although the epicentre has somewhat shifted. Data colonialism involves not one pole of colonial power (‘the West’), but at least two: the USA and China. This complicates our notion of the geography of the Global South, a concept which until now helped situate resistance and disidentification along geographic divisions between former colonizers and colonized. Instead, the new data colonialism works both externally — on a global scale — and internally on its own home populations. The elites of data colonialism (think of Facebook) benefit from colonization in both dimensions, and North-South, East-West divisions no longer matter in the same way.

It is important to acknowledge both the apparent similarities and the significant differences between our argument and the many preceding critical arguments about Big Data…(More)”

Technology, Activism, and Social Justice in a Digital Age


Book edited by John G. McNutt: “…offers a close look at both the present nature and future prospects for social change. In particular, the text explores the cutting edge of technology and social change, while discussing developments in social media, civic technology, and leaderless organizations — as well as more traditional approaches to social change.

It effectively assembles a rich variety of perspectives to the issue of technology and social change; the featured authors are academics and practitioners (representing both new voices and experienced researchers) who share a common devotion to a future that is just, fair, and supportive of human potential.

They come from the fields of social work, public administration, journalism, law, philanthropy, urban affairs, planning, and education, and their work builds upon 30-plus years of research. The authors’ efforts to examine changing nature of social change organizations and the issues they face will help readers reflect upon modern advocacy, social change, and the potential to utilize technology in making a difference….(More)”

From Code to Cure


David J. Craig at Columbia Magazine: “Armed with enormous amounts of clinical data, teams of computer scientists, statisticians, and physicians are rewriting the rules of medical research….

The deluge is upon us.

We are living in the age of big data, and with every link we click, every message we send, and every movement we make, we generate torrents of information.

In the past two years, the world has produced more than 90 percent of all the digital data that has ever been created. New technologies churn out an estimated 2.5 quintillion bytes per day. Data pours in from social media and cell phones, weather satellites and space telescopes, digital cameras and video feeds, medical records and library collections. Technologies monitor the number of steps we walk each day, the structural integrity of dams and bridges, and the barely perceptible tremors that indicate a person is developing Parkinson’s disease. These are the building blocks of our knowledge economy.

This tsunami of information is also providing opportunities to study the world in entirely new ways. Nowhere is this more evident than in medicine. Today, breakthroughs are being made not just in labs but on laptops, as biomedical researchers trained in mathematics, computer science, and statistics use powerful new analytic tools to glean insights from enormous data sets and help doctors prevent, treat, and cure disease.

“The medical field is going through a major period of transformation, and many of the changes are driven by information technology,” says George Hripcsak ’85PS,’00PH, a physician who chairs the Department of Biomedical Informatics at Columbia University Irving Medical Center (CUIMC). “Diagnostic techniques like genomic screening and high-resolution imaging are generating more raw data than we’ve ever handled before. At the same time, researchers are increasingly looking outside the confines of their own laboratories and clinics for data, because they recognize that by analyzing the huge streams of digital information now available online they can make discoveries that were never possible before.” …

Consider, for example, what the young computer scientist has been able to accomplish in recent years by mining an FDA database of prescription-drug side effects. The archive, which contains millions of reports of adverse drug reactions that physicians have observed in their patients, is continuously monitored by government scientists whose job it is to spot problems and pull drugs off the market if necessary. And yet by drilling down into the database with his own analytic tools, Tatonetti has found evidence that dozens of commonly prescribed drugs may interact in dangerous ways that have previously gone unnoticed. Among his most alarming findings: the antibiotic ceftriaxone, when taken with the heartburn medication lansoprazole, can trigger a type of heart arrhythmia called QT prolongation, which is known to cause otherwise healthy people to suddenly drop dead…(More)”

Big Data Is Getting Bigger. So Are the Privacy and Ethical Questions.


Goldie Blumenstyk at The Chronicle of Higher Education: “…The next step in using “big data” for student success is upon us. It’s a little cool. And also kind of creepy.

This new approach goes beyond the tactics now used by hundreds of colleges, which depend on data collected from sources like classroom teaching platforms and student-information systems. It not only makes a technological leap; it also raises issues around ethics and privacy.

Here’s how it works: Whenever you log on to a wireless network with your cellphone or computer, you leave a digital footprint. Move from one building to another while staying on the same network, and that network knows how long you stayed and where you went. That data is collected continuously and automatically from the network’s various nodes.

Now, with the help of a company called Degree Analytics, a few colleges are beginning to use location data collected from students’ cellphones and laptops as they move around campus. Some colleges are using it to improve the kind of advice they might send to students, like a text-message reminder to go to class if they’ve been absent.

Others see it as a tool for making decisions on how to use their facilities. St. Edward’s University, in Austin, Tex., used the data to better understand how students were using its computer-equipped spaces. It found that a renovated lounge, with relatively few computers but with Wi-Fi access and several comfy couches, was one of the most popular such sites on campus. Now the university knows it may not need to buy as many computers as it once thought.

As Gary Garofalo, a co-founder and chief revenue officer of Degree Analytics, told me, “the network data has very intriguing advantages” over the forms of data that colleges now collect.

Some of those advantages are obvious: If you’ve got automatic information on every person walking around with a cellphone, your dataset is more complete than if you need to extract it from a learning-management system or from the swipe-card readers some colleges use to track students’ activities. Many colleges now collect such data to determine students’ engagement with their coursework and campus activities.

Of course, the 24-7 reporting of the data is also what makes this approach seem kind of creepy….

I’m not the first to ask questions like this. A couple of years ago, a group of educators organized by Martin Kurzweil of Ithaka S+R and Mitchell Stevens of Stanford University issued a series of guidelines for colleges and companies to consider as they began to embrace data analytics. Among other principles, the guidelines highlighted the importance of being transparent about how the information is used, and ensuring that institutions’ leaders really understand what companies are doing with the data they collect. Experts at New America weighed in too.

I asked Kurzweil what he makes of the use of Wi-Fi information. Location tracking tends toward the “dicey” side of the spectrum, he says, though perhaps not as far out as using students’ social-media habits, health information, or what they check out from the library. The fundamental question, he says, is “how are they managing it?”… So is this the future? Benz, at least, certainly hopes so. Inspired by the Wi-Fi-based StudentLife research project at Dartmouth College and the experiences Purdue University is having with students’ use of its Forecast app, he’s in talks now with a research university about a project that would generate other insights that might be gleaned from students’ Wi-Fi-usage patterns….(More)

Predicting Public Interest Issue Campaign Participation on Social Media


Jungyun Won, Linda Hon, Ah Ram Lee in the Journal of Public Interest Communication: “This study investigates what motivates people to participate in a social media campaign in the context of animal protection issues.

Structural equation modeling (SEM) tested a proposed research model with survey data from 326 respondents.

Situational awareness, participation benefits, and social ties influence were positive predictors of social media campaign participation intentions. Situational awareness also partially mediates the relationship between participation benefits and participation intentions as well as strong ties influence and participation intentions.

When designing social media campaigns, public interest communicators should raise situational awareness and emphasize participation benefits. Messages shared through social networks, especially via strong ties, also may be more effective than those posted only on official websites or social networking sites (SNSs)….(More)”.

Ethics as Methods: Doing Ethics in the Era of Big Data Research—Introduction


Introduction to the Special issue of Social Media + Society on “Ethics as Methods: Doing Ethics in the Era of Big Data Research”: Building on a variety of theoretical paradigms (i.e., critical theory, [new] materialism, feminist ethics, theory of cultural techniques) and frameworks (i.e., contextual integrity, deflationary perspective, ethics of care), the Special Issue contributes specific cases and fine-grained conceptual distinctions to ongoing discussions about the ethics in data-driven research.

In the second decade of the 21st century, a grand narrative is emerging that posits knowledge derived from data analytics as true, because of the objective qualities of data, their means of collection and analysis, and the sheer size of the data set. The by-product of this grand narrative is that the qualitative aspects of behavior and experience that form the data are diminished, and the human is removed from the process of analysis.

This situates data science as a process of analysis performed by the tool, which obscures human decisions in the process. The scholars involved in this Special Issue problematize the assumptions and trends in big data research and point out the crisis in accountability that emerges from using such data to make societal interventions.

Our collaborators offer a range of answers to the question of how to configure ethics through a methodological framework in the context of the prevalence of big data, neural networks, and automated, algorithmic governance of much of human socia(bi)lity…(More)”.