Smartphones as Locative Media


Book by Jordan Frith: “Smartphone adoption has surpassed 50% of the population in more than 15 countries, and there are now more than one million mobile applications people can download to their phones. Many of these applications take advantage of smartphones as locative media, which is what allows smartphones to be located in physical space. Applications that take advantage of people’s location are called location-based services, and they are the focus of this book.

Smartphones as locative media raise important questions about how we understand the complicated relationship between the Internet and physical space. This book addresses these questions through an interdisciplinary theoretical framework and a detailed analysis of how various popular mobile applications including Google Maps, Facebook, Instagram, Yelp, and Foursquare use people’s location to provide information about their surrounding space….(More)”

This Is What Controversies Look Like in the Twittersphere


Emerging Technology From the arXiv: “A new way of analyzing disagreement on social media reveals that arguments in the Twittersphere look like fireworks.

Many a controversy has raged on social media platforms such as Twitter. Some last for weeks or months, others blow themselves in an afternoon. And yet most go unnoticed by most people. That would change if there was a reliable way of spotting controversies in the Twitterstream in real time.

That could happen thanks to the work of Kiran Garimella and pals at Aalto University in Finland. These guys have found a way to spot the characteristics of a controversy in a collection of tweets and distinguish this from a noncontroversial conversation.

Various researchers have studied controversies on Twitter but these have all focused on preidentified arguments, whereas Garimella and co want to spot them in the first place. Their key idea is that the structure of conversations that involve controversy are different from those that are benign.

And they think this structure can be spotted by studying various properties of the conversation, such as the network of connections between those involved in a topic; the structure of endorsements, who agrees with whom; and the sentiment of the discussion, whether positive and negative.

They test this idea by first studying ten conversations associated with hashtags that are known to be controversial and ten that are known to be benign. Garimella and co map out the structure of these discussion by looking at the networks of retweets, follows, keywords and combinations of these….(More)

More: arxiv.org/abs/1507.05224 : Quantifying Controversy in Social Media

Transparency in Social Media


New book on “Tools, Methods and Algorithms for Mediating Online Interactions” edited by Matei, Sorin; Adam; Russell Martha G.: and Bertino, Elisa (Eds.): “The volume presents, in a synergistic manner, significant theoretical and practical contributions in the area of social media reputation and authorship measurement, visualization, and modeling. The book justifies and proposes contributions to a future agenda for understanding the requirements for making social media authorship more transparent. Building on work presented in a previous volume of this series, Roles, Trust, and Reputation in Social Media Knowledge Markets, this book discusses new tools, applications, services, and algorithms that are needed for authoring content in a real-time publishing world. These insights may help people who interact and create content through social media better assess their potential for knowledge creation. They may also assist in analyzing audience attitudes, perceptions, and behavior in informal social media or in formal organizational structures. In addition, the volume includes several chapters that analyze the higher order ethical, critical thinking, and philosophical principles that may be used to ground social media authorship. Together, the perspectives presented in this volume help us understand how social media content is created and how its impact can be evaluated.

The chapters demonstrate thought leadership through new ways of constructing social media experiences and making traces of social interaction visible. Transparency in Social Media aims to help researchers and practitioners design services, tools, or methods of analysis that encourage a more transparent process of interaction and communication on social media. Knowing who has added what content and with what authority to a specific online social media project can help the user community better understand, evaluate and make decisions and, ultimately, act on the basis of such information …(More)”

Citizen Sensor Data Mining, Social Media Analytics and Applications


Paper by Amit P. Sheth: “With the rapid rise in the popularity of social media (1B+ Facebook users, 200M+ twitter users), and near ubiquitous mobile access (4+ billion actively-used mobile phones), the sharing of observations and opinions has become common-place (500M+ tweets a day). This has given us an unprecedented access to the pulse of a populace and the ability to perform analytics on social data to support a variety of socially intelligent applications — be it for brand tracking and management, crisis coordination, organizing revolutions or promoting social development in underdeveloped and developing countries. I will review: 1) understanding and analysis of informal text, esp. microblogs (e.g., issues of cultural entity extraction and role of semantic/background knowledge enhanced techniques), and 2) how we built Twitris, a comprehensive social media analytics (social intelligence) platform. I will describe the analysis capabilities along three dimensions: spatio-temporal-thematic, people-content-network, and sentiment-emption-intent. I will couple technical insights with identification of computational techniques and real-world examples using live demos of Twitris….(More)”

The data or the hunch


Ian Leslie at Intelligent Life: “THE GIFT FOR talent-spotting is mysterious, highly prized and celebrated. We love to hear stories about the baseball coach who can spot the raw ability of an erratic young pitcher, the boss who sees potential in the guy in the post room, the director who picks a soloist out of the chorus line. Talent shows are a staple of the TV schedules. We like to believe that certain people—sometimes ourselves—can just sense when a person has something special. But there is another method of spotting talent which doesn’t rely on hunches. In place of intuition, it offers data and analysis. Rather than relying on the gut, it invites us to use our heads. It tends not to make for such romantic stories, but it is effective—which is why, despite our affection, the hunch is everywhere in retreat.

Strike one against the hunch was the publication of “Moneyball” by Michael Lewis (2003), which has attained the status of a management manual for many in sport and beyond. Lewis reported on a cash-strapped major-league baseball team, the Oakland A’s, who enjoyed unlikely success against bigger and better-funded competitors. Their secret sauce was data. Their general manager, Billy Beane, had realised that when it came to evaluating players, the gut instincts of experienced baseball scouts were unreliable, and he employed statisticians to identify talent overlooked by the big clubs…..

These days, when a football club is interested in a player, it considers the average distance he runs in a game, the number of passes and tackles or blocks he makes, his shots on goal, the ratio of goals to shots, and many other details nobody thought to measure a generation ago. Sport is far from the only industry in which talent-spotting is becoming a matter of measurement. Prithwijit Mukerji, a postgraduate at the University of Westminster in London, recently published a paper on the way the music industry is being transformed by “the Moneyball approach”. By harvesting data from Facebook and Twitter and music services like Spotify and Shazam, executives can track what we are listening to in far more detail than ever before, and use it as a guide to what we will listen to next….

This is the day of the analyst. In education, academics are working their way towards a reliable method of evaluating teachers, by running data on test scores of pupils, controlled for factors such as prior achievement and raw ability. The methodology is imperfect, but research suggests that it’s not as bad as just watching someone teach. A 2011 study led by Michael Strong at the University of California identified a group of teachers who had raised student achievement and a group who had not. They showed videos of the teachers’ lessons to observers and asked them to guess which were in which group. The judges tended to agree on who was effective and ineffective, but, 60% of the time, they were wrong. They would have been better off flipping a coin. This applies even to experts: the Gates Foundation funded a vast study of lesson observations, and found that the judgments of trained inspectors were highly inconsistent.

THE LAST STRONGHOLD of the hunch is the interview. Most employers and some universities use interviews when deciding whom to hire or admit. In a conventional, unstructured interview, the candidate spends half an hour or so in a conversation directed at the whim of the interviewer. If you’re the one deciding, this is a reassuring practice: you feel as if you get a richer impression of the person than from the bare facts on their résumé, and that this enables you to make a better decision. The first theory may be true; the second is not.

Decades of scientific evidence suggest that the interview is close to useless as a tool for predicting how someone will do a job. Study after study has found that organisations make better decisions when they go by objective data, like the candidate’s qualifications, track record and performance in tests. “The assumption is, ‘if I meet them, I’ll know’,” says Jason Dana, of Yale School of Management, one of many scholars who have looked into the interview’s effectiveness. “People are wildly over-confident in their ability to do this, from a short meeting.” When employers adopt a holistic approach, combining the data with hunches formed in interviews, they make worse decisions than they do going on facts alone….” (More)

Geek Heresy


Book by Kentaro Toyama “…, an award-winning computer scientist, moved to India to start a new research group for Microsoft. Its mission: to explore novel technological solutions to the world’s persistent social problems. Together with his team, he invented electronic devices for under-resourced urban schools and developed digital platforms for remote agrarian communities. But after a decade of designing technologies for humanitarian causes, Toyama concluded that no technology, however dazzling, could cause social change on its own.

Technologists and policy-makers love to boast about modern innovation, and in their excitement, they exuberantly tout technology’s boon to society. But what have our gadgets actually accomplished? Over the last four decades, America saw an explosion of new technologies – from the Internet to the iPhone, from Google to Facebook – but in that same period, the rate of poverty stagnated at a stubborn 13%, only to rise in the recent recession. So, a golden age of innovation in the world’s most advanced country did nothing for our most prominent social ill.

Toyama’s warning resounds: Don’t believe the hype! Technology is never the main driver of social progress. Geek Heresy inoculates us against the glib rhetoric of tech utopians by revealing that technology is only an amplifier of human conditions. By telling the moving stories of extraordinary people like Patrick Awuah, a Microsoft millionaire who left his lucrative engineering job to open Ghana’s first liberal arts university, and Tara Sreenivasa, a graduate of a remarkable South Indian school that takes children from dollar-a-day families into the high-tech offices of Goldman Sachs and Mercedes-Benz, Toyama shows that even in a world steeped in technology, social challenges are best met with deeply social solutions….(More)”

Using Twitter as a data source: An overview of current social media research tools


Wasim Ahmed at the LSE Impact Blog: “I have a social media research blog where I find and write about tools that can be used to capture and analyse data from social media platforms. My PhD looks at Twitter data for health, such as the Ebola outbreak in West Africa. I am increasingly asked why I am looking at Twitter, and what tools and methods there are of capturing and analysing data from other platforms such as Facebook, or even less traditional platforms such as Amazon book reviews. Brainstorming a couple of responses to this question by talking to members of the New Social Media New Social Science network, there are at least six reasons:

  1. Twitter is a popular platform in terms of the media attention it receives and it therefore attracts more research due to its cultural status
  2. Twitter makes it easier to find and follow conversations (i.e., by both its search feature and by tweets appearing in Google search results)
  3. Twitter has hashtag norms which make it easier gathering, sorting, and expanding searches when collecting data
  4. Twitter data is easy to retrieve as major incidents, news stories and events on Twitter are tend to be centred around a hashtag
  5. The Twitter API is more open and accessible compared to other social media platforms, which makes Twitter more favourable to developers creating tools to access data. This consequently increases the availability of tools to researchers.
  6. Many researchers themselves are using Twitter and because of their favourable personal experiences, they feel more comfortable with researching a familiar platform.

It is probable that a combination of response 1 to 6 have led to more research on Twitter. However, this raises another distinct but closely related question: when research is focused so heavily on Twitter, what (if any) are the implications of this on our methods?

As for the methods that are currently used in analysing Twitter data i.e., sentiment analysis, time series analysis (examining peaks in tweets), network analysis etc., can these be applied to other platforms or are different tools, methods and techniques required? In addition to qualitative methods such as content analysis, I have used the following four methods in analysing Twitter data for the purposes of my PhD, below I consider whether these would work for other social media platforms:

  1. Sentiment analysis works well with Twitter data, as tweets are consistent in length (i.e., <= 140) would sentiment analysis work well with, for example Facebook data where posts may be longer?
  2. Time series analysis is normally used when examining tweets overtime to see when a peak of tweets may occur, would examining time stamps in Facebook posts, or Instagram posts, for example, produce the same results? Or is this only a viable method because of the real-time nature of Twitter data?
  3. Network analysis is used to visualize the connections between people and to better understand the structure of the conversation. Would this work as well on other platforms whereby users may not be connected to each other i.e., public Facebook pages?
  4. Machine learning methods may work well with Twitter data due to the length of tweets (i.e., <= 140) but would these work for longer posts and for platforms that are not text based i.e., Instagram?

It may well be that at least some of these methods can be applied to other platforms, however they may not be the best methods, and may require the formulation of new methods, techniques, and tools.

So, what are some of the tools available to social scientists for social media data? In the table below I provide an overview of some the tools I have been using (which require no programming knowledge and can be used by social scientists):…(More)”

India PM releases ‘official Narendra Modi app’


David Reid at The Telegraph: “Narendra Modi, the Indian prime minister, who is already the third most popular world leader on Twitter, has extended his reach on social media by launching his own mobile app.

The app gives users regular updates on Mr Modi’s movements, and includes blog posts, interviews and “messages from the PM”….

Users can listen live to the Indian prime minister’s regular radio show, Mann Ki Baat and read about Mr Modi’s rise from “humble beginnings” on the biography section.

Another article explains why Mr Modi “opposes move to include his life story in school syllabus”.

A loyalty scheme rewards supporters with points and badges for filling out questionnaires and listening to Mr Modi’s speeches.

Mr Modi, who has 13 million followers on Twitter, is not the first politician to launch a personal app, although they are usually reserved for campaigning.

As well as Twitter, Mr Modi also has Facebook, Pinterest and YouTube accounts and his own website….(More)

Using social media in hotel crisis management: the case of bed bugs


Social media has helped to bridge the communication gap between customers and hotels. Bed bug infestations are a growing health crisis and have obtained increasing attention on social media sites. Without managing this crisis effectively, bed bug infestation can cause economic loss and reputational damages to hotel properties, ranging from negative comments and complaints, to possible law suits. Thus, it is essential for hoteliers to understand the importance of social media in crisis communication, and to incorporate social media in hotels’ crisis management plans.

This study serves as one of the first attempts in the hospitality field to offer discussions and recommendations on how hotels can manage the bed bug crisis and other crises of this kind by incorporating social media into their crisis management practices….(More)”

Data, Human Rights & Human Security


Paper by Mark Latonero and  Zachary Gold“In today’s global digital ecosystem, mobile phone cameras can document and distribute images of physical violence. Drones and satellites can assess disasters from afar. Big data collected from social media can provide real-time awareness about political protests. Yet practitioners, researchers, and policymakers face unique challenges and opportunities when assessing technological benefit, risk, and harm. How can these technologies be used responsibly to assist those in need, prevent abuse, and protect people from harm?”

Mark Latonero and Zachary Gold address the issues in this primer for technologists, academics, business, governments, NGOs, intergovernmental organizations — anyone interested in the future of human rights and human security in a data-saturated world….(Download PDF)”