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Yelena Mejova, Ingmar Weber and Michael Macy (eds) (2015), Twitter: A Digital Socioscope, Cambridge: Cambridge University Press

Yelena Mejova, Ingmar Weber and Michael Macy (eds) (2015), Twitter: A Digital Socioscope, Cambridge: Cambridge University Press 183pp.
ISBN: 978-1-107-10237-8 (hardback), 978-1-107-50007-5 (paperback)

Review by Marco Del Vecchio, Department of Statistics, University of Warwick

The complexity of everyday social life has a two-fold effect on social science research. On the one hand, human societies have managed to keep social scientists engaged in understanding this complexity for centuries. On the other, as everyday social life changes, so does the complexity; the advent of globalisation has made it incredibly difficult - or even impossible - to observe social interactions at the population level. As a result, most surveys rely on samples containing independent observations which do not take into consideration peer influence (p. 3). Twitter: A Digital Socioscope, edited by Yelena Mejova, Ingmar Weber and Michael Macy, walks the reader though the most recent applications of Twitter data to study human behaviour and social interactions. Consisting of six independent chapters composed by leading domain experts, the book presents a diverse and engaging mixture of case studies which cover political opinion (Chapter 2), socio-economic indicators (Chapter 3), happiness (Chapter 4), public health (Chapter 5) and disaster monitoring (Chapter 6).

Most social scientists might already have an understanding of how social media data could have a profound effect on the quality and richness of their research. The authors are nevertheless aware that the reader might not possess the technical background needed to accesses this data (pp. 13-14). The book therefore begins with a rather extensive section on the tools available to access Twitter data via its application program interfaces (APIs). While this reviewer was pleased with the clarity and attention to detail which characterised the sections on aggregating and enriching twitter data, user profiling and bias identification, he would have liked to be provided with more examples related to the programming side of the subject matter. As a case in point, I find that the only two coding examples aimed at showing an application of a MapReduce algorithm do not balance the amount of theory proposed in the previous pages. In fact, I believe that the reader would benefit from having examples outlining, inter alia, how to connect to the Twitter Streaming API and target relevant tweets.

Twitter sentiment analysis (TSA) has become a hot research topic in recent years and the book does not fail to underline its importance by providing insightful TSA applications in topics such as political opinion, consumer confidence, social mood, investor sentiment, public health and disaster response and recovery. Yet, although covering the two main approaches for TSA, i.e. lexicon and machine learning-based methods, it glosses over the importance that emoticons analysis has on increasing the quality of opinion mining. For instance, Liu, and others (2012: 1678) took a supervised approach to TSA and complemented it with the use of emoticons for leveraging the manually labelled data. Liu and others (2012: 1683) suggested that and found that their method of examining emoticons within Twitter use could 'effectively integrate both kinds of data to outperform those methods using only one of them'.

While Twitter: A Digital Socioscope is more an introduction to the methods, opportunities and challenges of utilising Twitter data for socio-economic research, it does not ignore some important issues related to sample representativeness, tweets' trustworthiness and the correlation-causation critique often present wherever explorative data analysis is made. Overall, the editors and authors have successfully compiled a book that is both insightful and useful. The breadth of topics covered makes me willing to recommend it to anyone who wants to gain a general understanding of Twitter's role in computational social science.

References

Liu, K. L., W.J. Li and M. Guo (2012), 'Emoticon Smoothed Language Models for Twitter Sentiment Analysis', Association for the Advancement of Artificial Intelligence, http://cs.nju.edu.cn/lwj/paper/AAAI12_ESLAM.pdf, accessed 23 March 2016

Review by Casimir MacGregor, School of Social Science, Monash University

'Think globally, act locally' has been the catch-cry of the environmental sustainability and more recently the anti-globalisation movement over the past few decades. But it was perhaps not until the emergence of social media that such a phrase became part of everyday practice. Social media has changed the way people interact socially, and the ways in which they consume and create knowledge. Twitter celebrated its tenth birthday recently; the first ever tweet was by Jack Dorsey (Twitter's co-founder) 'just setting up my twttr' at 7.50am, 22 March 2006. Since that day Twitter has become the social medium of choice (in 140 characters or less); it has amassed approximately 320 million users, creates 500 million tweets per day and generates more than $US 500 million per quarter in revenue (Greenberg, 2016). So it is therefore timely that the authors of this edited volume have sought to help demonstrate the social significance of Twitter to our everyday social and global relations.

The book comprises scholarship in the emerging field of computational social science that seeks to 'illustrate the possibilities, advantages, and limitations of large, semi-structured social media data to gain insights into human behaviour' (p. ix). The book's subtitle, a 'digital socioscope', is a potent metaphor of the book's intent; like a telescope that revolutionised the study of astronomy, it is argued that Twitter (and other social media / web 2.0) should become a tool to examine individual interactions and global events and to enable research to address fundamental sociological questions relating to social identity, status, conflict and knowledge. The book sets out to examine these themes in its six chapters. The first three chapters outline how Twitter should be analysed (Chapter 1) and how it can be used as a tool to examine political opinion (Chapter 2) and socio-economic indicators (Chapter 3). The language of Twitter and measuring of user sentiment, especially happiness, is the focus of Chapter 4. Chapters 5 and 6 (which I think are some of the most interesting) seek to demonstrate how Twitter was used to predict an influenza pandemic and how it was used as a source for public information and means of engaging with communities during disaster response and recovery.

The book's strength is its attempt at providing an excellent overview of the key tools, skills, and case studies that demonstrate the value of Twitter as way to examine and understand social practice. Despite this there are a couple of shortcomings that could have been developed to enhance this excellent collection. The first is the book's academic style and use of extensive use of quantitative data in some chapters, which could be challenging for some readers. As a social anthropologist who has also used social media in my own research (see Petersen et al., 2015), I would have liked to see more stories and narratives related to the use of Twitter. For example, how is Twitter used to help create new forms of experience? In our research into the use of social media among patient activists considering unproven stem cell therapy, we demonstrated how new media, such as Twitter, has become an essential tool that is profoundly changing the meanings and practices of health and healthcare. This includes the notion of 'the patient', traditionally conceived as the passive recipient of information, advice, treatment and care, and 'the expert', the presumed possessor and dispenser of privileged knowledge and practice gained through a wealth of experience. Social networking via new media, such as Twitter, has introduced a new dimension into physician-patient interaction, that has created new manifestations of patient activism that involve an active engagement with accredited experts and expertise, as well as with forms of knowledge and practice that exist at the margins of conventional biomedicine that help to create 'communities of hope' which create optimistic 'framings' of particular treatments and conceptions of risk (Petersen et al., 2015). I would argue that in attempting to outline a digital sociocope, it is critical that scholars also attend to the stories and experiences of producers and consumers of social media, in order to see how these new digital technologies are re-shaping human experience.

Another key omission from the book is an in-depth examination of the 'Twitter revolutions', such as the so-called Arab Spring. Although these events are mentioned in the text, their key sociological impact is never explored meaningfully in any great detail. As Sullivan (2012: 773) notes, the use of Twitter to affect political change and its role in empowering activists and dissidents in societies such as Iran, Tunisia and Moldova, has been dubbed by some as a largely a 'media-driven manifestation of cyber utopianism'. It would therefore have been useful to examine critically how Twitter has been used in countries such as North Korea, China and Iran, where it is banned. By examining the use of Twitter in social contexts that restrict or prohibit its use, it would add another critical dimension to the examination of Twitter as a digital socioscope. Considering that Twitter's users are predominately from high- and middle-income countries, it makes sense to examine the use of Twitter in cross-cultural contexts or else all we are viewing are the thoughts and concerns of the elites. Twitter has been part of the digital revolution that has democratised technology - it is therefore essential we include within the digital socioscope the voices of those at the margins and not solely the majority.

References

Greenberg, J. (2016), 'On its 10th birthday, a short history of twitter in tweets', Wired Magazine, 21 March, http://www.wired.com/2016/03/10th-birthday-short-history-twitter-tweets, accessed 22 March 2016

Petersen, A., C. MacGregor and M. Munsie (2015), 'Stem Cell Miracles or Russian Roulette? Use of Digital Media to Campaign for Access to Clinically Unproven Treatments' Health, Risk and Society 17 (7-8), 592-604

Sullivan, J. (2012), 'A Tale of Two Microblogs in China', Media, Culture & Society, 34 (6), 773-83


 

To cite either of these reviews please use the following details: Del Vecchio, M OR MacGregor, C. (2016), Yelena Mejova, Ingmar Weber and Michael Macy (eds) (2015), Twitter: A Digital Socioscope, Reinvention: an International Journal of Undergraduate Research, Volume 9, Issue 1, http://www.warwick.ac.uk/reinventionjournal/archive/volume9issue1/delvecchioandmacgregor Date accessed [insert date]. If you cite these reviews or use them in any teaching or other related activities please let us know by e-mailing us at Reinventionjournal at warwick dot ac dot uk.