Can we generalize from one social media platform to another?


One of the things my dissertation, Emotion in Social Media, highlights is the importance of the comparative perspective in social media research. I looked at three big questions in the field, proposing the same hypotheses for both Facebook and Twitter — but ended up drawing some conclusions that were pretty divergent and unique to each service.

My dissertation examines (1) the emotions we express in social media (i.e. the emotional profile of the status update), (2) what we can infer about someone’s emotional life in general based on what they say in their status updates (and possible limitations on those inferences), and (3) the emotional experience of browsing social media (Do we get riled up? Envy our friends’ lives?). I searched far and wide in my literature review — and took note of a handful of related studies that analyzed more than one social media service — but saw little to support the idea that Facebook and Twitter were fundamentally different in terms of emotional expression, emotional inference, or emotional experience. Indeed, many studies drew conclusions about ‘social media’ based on an analysis of just one service.

It’s true that if you read my dissertation, you might walk away with the impression that Facebook and Twitter share some important things in common. Status updates on both services are characterized by elevated arousal and higher levels of emotions like amusement, anger, surprise and awe that are more wound up. You’ll find that status updates on both services appear to provide something of a window into our emotional lives, though the association is not especially tight, is moderated by factors like how emotionally stable we are, and disappears entirely when the popular sentiment analysis program Linguistic Inquiry and Word Count (LIWC) is used to analyze the emotional contents of status updates. You’ll also find that the most robust effect of browsing both services appears to be that people tend to wind down (i.e. feel more relaxed, sleepy, bored, etc.), not wind up, as the stereotype goes.

That’s a lot in common. But in synthesizing the literature review for my dissertation, I noted a broad chain of reasoning that seemed to link the literature together, even if it was never fully articulated by any one researcher. This “overarching hypothesis” about emotion in social media goes something like this: Status updates are overly-positive, reflecting a concern for self-presentation, which in turn limits how valid status updates are for inferring our day-to-day emotional lives, and which ultimately causes us to feel envy while we browse social media.

In results, this entire chain of reasoning receives at least some support, but for Facebook only. Facebook posts are more positive than day-to-day emotional life, self-presentation concerns do seem to moderate the association between Facebook posts and emotional life, while browsing Facebook is characterized by some elevation in envy. There are limits to each link in the chain — self-presentation concerns do not eliminate the association between Facebook posts and emotional life, for example — but every link is nonetheless supported.

Interestingly, however, the overarching hypothesis receives little support for Twitter. Tweets are more negative than day-to-day emotional life, self-presentation concerns largely do not moderate the association between tweets and emotional experience, and envy might actually be alleviated while we browse Twitter. A lesson of this dissertation, therefore, may be about the importance of comparative perspectives in social media research. Key social psychological dynamics that characterize one service, like Facebook, may not generalize to another, like Twitter, even when they share the same core design, i.e. feeds of status updates.

Next time you hear someone talk about “social media” as though all services have uniform, monolithic implications for behavior, you might nudge them to consider that different services can create different, unique contexts — with potentially divergent implications for behavior.

Galen Panger received his Ph.D. from Berkeley in 2017, focusing on social media behavior, happiness and well-being, and behavioral economics. He is currently a user experience researcher at Google. Panger will be honored at iConference 2018 as the 2018 winner of the iSchools Doctoral Dissertation Award.


Exploring serendipity: Information encounters and their practical legal impact


Law is a highly information intensive profession.1 To provide proficient legal services to their clients, lawyers must command the applicable law and judicial resolutions governing the issue in question, on a continuous basis. However, the basic step of finding a leading case involving an issue is in many cases actually difficult to attain.2 This is the case for Israeli family-law attorneys, who practice law in a challenging information environment which lacks published Family and Religious Courts rulings as they are being conducted behind closed-doors, thus maintaining a body of ‘secret law’.3

In light of a profound notion that information researchers can and should generate theoretical and applied knowledge in this matter, I explored various aspects of serendipity—i.e. fortunate discoveries by accidents and sagacity, of things a person is not in quest of,4 in the legal (i.e. professional) information seeking behavior of Israeli family-law attorneys. My master’s thesis research (conducted under the supervision of Dr. Jenny Bronstein, Bar-Ilan University) has provided a detailed examination of these attorneys’ memorable experiences of accidental, unexpected encounters with useful Family and Religious Courts rulings.5

Quantitative data from 135 Israeli family-law attorneys were collected using an online questionnaire, and used for analysis. Some of the findings that I find most interesting are that Israeli family-law attorneys reported regularly encountering with Family and Religious Courts rulings on their professional practice, and also relying on such accidental, unexpected encounters as a way of obtaining professional information; thus I identified them as ‘super-encounterers’, in-line with Erdelez’s6 theoretical framework.

Furthermore, the study also succeeded in identifying seven distinctive professional contributions—that represent the value of these information encounters in the ongoing legal practice—spanning, inter alia, from establishment or expansion of a private collection of court rulings; through manifestation of an additional, or different, thinking course or reasoning; to support for an argument claimed, or considered to be claimed, on behalf a client or contradiction of an argument claimed by the adverse party.5 To wit, information encountering with out-of-sight court rulings were found to build up family-law attorneys’ competence to keep up with current understanding and interpretation of the law, and better serve their clients.5 I concluded my research by providing several practical measures that may possibly increase chances for serendipity to occur in attorney’s legal information seeking behavior5:126-127; among others, the findings can guide lawyers in legal information sources selection and use, assist them in detecting mishandled information sources, and provide insights for refining academic and continuing legal research and information seeking training.

Figure 1: Professional contributions of the unexpected and valuable encounters with Family and Religious Courts rulings.

Forward-looking, this study of nonlinear information seeking behavior, as well as other humanities-initiated empirical research of-, and within-, the legal domain, may be competent assistive instruments for fostering true changes to legal practices, with an ensuing potential impact on justice dissemination in the society.

Click here to view references 1-6.
Click here to view the full research.

Yosef Solomon

Yosef Solomon

Yosef Solomon is a licensed lawyer (Israel), and a doctoral researcher in the Department of Information Science, Bar-Ilan University. His primary research interests include human information behavior, information studies in the arts, information in the legal profession, and serendipity. Yosef participated in the iSchools iConference 2017 Doctoral Colloquium, and will present a poster in the upcoming iConference 2018 in Sheffield, UK.


Exploring Fine-Grained Emotion Detection in Microblog Text


Endowing computers with the ability to recognize emotions in text has important applications in the field of information science. Over a decade of research in sentiment analysis on Twitter, a popular microblogging site, has allowed large amounts of tweets (i.e., Twitter posts) to be harnessed to predict stock market trends1, measure the population’s level of happiness2, detect clinical depression3 and to augment our ability to understand emotions expressed in text. However, existing automatic emotion detectors analyze text at a coarse-grained level (positive or negative) or detect only a small set of emotions (happiness, sadness, fear, anger, disgust and surprise). I argue that there is a richer range of emotion expressed in microblog text that computers can be trained to detect. By training automatic emotion detectors to recognize a greater number of emotions, it is possible to create more emotion-sensitive systems that can enhance our interaction with computers as well as our understanding of human emotions in online interactions.

I embarked on a journey through my dissertation4 to uncover a set of emotion categories that are representative of the emotions expressed and described in tweets. An important starting point to build supervised machine learning models that can recognize the emotions represented in tweets is the identification of a set of suitable emotion categories. Realistically, this set of categories should be a set of emotion categories humans can reliably detect from tweets. What emotions can humans detect in microblog text? How do current machine learning techniques perform on more fine-grained categories of emotion?

To address the questions, I first applied content analysis to uncover a set of fine-grained emotions humans can detect in microblog text. A corpus (EmoTweet-28) of 15,553 tweets5 were annotated for emotion in two phases. In Phase 1, grounded theory was applied on a group of trained annotators, wherein the annotators were not supplied with a predefined set of emotion category labels. They were instructed to suggest emotion tags most suited to describe the emotion expressed in a tweet. A total of 246 emotion tags were proposed, which were then systematically reduced to 28 emotion categories. The 28 emotion categories that emerged in Phase 1 were further tested through large-scale content analysis using Amazon Mechanical Turk to determine how representative the emotion categories were of the range of emotions expressed on Twitter. Phase 3 focused on running a series of machine learning experiments to assess machine performance in the detection of the 28 emotion categories.

Figure 1: Human performance (Kappa) versus machine performance (F1)

Human performance, measured by class distinctiveness (inter-annotator reliability in Kappa per class), and machine performance, measured by F1 (harmonic mean between precision and recall for each class), are shown in Figure 1. Human performance and machine performance vary across the 28 emotion categories. With exception of “exhaustion”, the machine learning models achieved relatively higher performance compared to human reliability in recognizing all other emotion categories. Machine performance and human performance differ less for the emotion categories on the farther left of Figure 1 (e.g., “anger” and “indifference”). The emotion categories on the farther right of Figure 1 (e.g., “sympathy”, “pride” and “inspiration”) demonstrate better machine performance compared to human performance. One emotion category, “gratitude” achieved consistently high machine and human performance.

I have demonstrated that it is feasible to extend machine learning classification to fine-grained emotion detection (i.e., as many as 28 emotion categories). The real strength of machine learning classifier lies in its capability to reliably detect some of the emotion categories that are difficult for the humans to recognize (e.g., “sympathy”, “hate” and “hope”). The way I see it, my dissertation is a first step to pave the way towards the development of more emotion-sensitive systems. I will continue my quest to test the applicability of the emotion categories in other types of text and improve the performance of the machine learning models for fine-grained emotion detection in other domains and applications.

Click here to view references 1-5.

Dr. Jasy Liew Suet Yan

Jasy Liew Suet Yan is a Senior Lecturer at the School of Computer Sciences, University of Science Malaysia. She graduated with a Ph.D. from the School of Information Studies, Syracuse University in 2016. Her research focuses on using natural language processing (NLP) techniques to detect expressions of emotion in text; her broader research interests include sentiment analysis, computational linguistics and affective computing. Click here for more. She was runner-up for the 2017 iSchools Doctoral Dissertation Award.


Social Trust in Internet Infrastructure


From its inception, the Internet has held the promise of creating more democratic societies, by bringing people across the world into conversation and closer relationships with each other. Yet it seems that hardly a day goes by without a data breach, concerns about “fake news”, or newly discovered vulnerabilities in the computer systems that we use every day. The contradiction between the hope and the reality of the Internet forces us to ask: how can we build an Internet that we can trust, and through which we can trust each other? And to what extent, and in what ways, is such an Internet possible? In my work, I engage with the problem of trust in the Internet through ethnographic research into the social relationships and practices involved in operating Internet infrastructure.

In our everyday use of the Internet, we often think of it as a single technological object, which mediates access to an array of services and content for billions of people across the world. But beneath this apparently seamless whole lies a complex global infrastructure, composed of tens of thousands of interconnected computer networks, operated by independent organizations, distributed across every country in the world. The creation of a secure and trustworthy Internet depends upon effective coordination of activity across these diverse technological systems, operated in a variety of social, economic, geographic, and political contexts.

Global governance institutions can address some of the problems in the coordination of Internet infrastructure. For example, the ICANN regime manages the allocation of critical Internet resources, and the IETF develops technical standards for the Internet. Contractual arrangements between organizations can also help resolve some of these coordination problems. However, as I found in my research, while governance institutions and contractual arrangements are necessary for the effective coordination of Internet infrastructure, they are insufficient in themselves.

By studying the practices of the technical personnel involved in the operation of Internet infrastructure across organizations in North America and South Asia, I discovered the essential role of interpersonal trust relationships in enabling coordination across organizational and territorial boundaries. Technical personnel who manage the interconnection of computer networks rely upon interpersonal trust relationships to manage a range of activity, from the stable operation of network interconnections, to the negotiation of market arrangements for these interconnections. Information security personnel rely upon interpersonal trust relationships to maintain the confidentiality of new vulnerabilities and emerging threats, while coordinating to respond to these issues. Organized technical communities and conferences (such as NANOG in North America, and SANOG in South Asia) offer critical sites through which practices and trust relationships are formed, and circulate within and across regions.

As my research shows, Internet infrastructure offers invaluable lessons for understanding the role of trust in operating a complex sociotechnical system. To create an Internet which supports trust, we must pay attention to the role of trust in the operation of infrastructure, as much as to the services, content, and users of the Internet.

Ashwin J. Mathew is an ethnographer of Internet infrastructure. His research is supported by positions at Packet Clearing House, the UC Berkeley School of Information, and the Slow Science Institute. Mathew was the winner of the iSchools Doctoral Dissertation Award for 2016.


Understanding Design Education in Librarianship


Although creating information tools and services is an integral aspect of the field, American librarianship is typically considered a social science. In my 2016 dissertation, I demonstrated that an alternative epistemological approach—that of design–is an appropriate framework for librarianship, offering opportunities for innovation, empowerment, and stronger explicit alignment with the values of the field.1 However, despite an increasing interest in design education in iSchools at large,2 there has previously been little explicit incorporation of design in formal graduate level library education programs; specifically American MLIS and equivalent degrees.

In the past year, one thread of my research agenda has been focused on this educational issue identified in my dissertation work. Building on a pilot study with data from the University of Washington’s iSchool,3 I solicited data from additional MLIS programs to understand the educational backgrounds of people who choose to pursue library education. Anecdotally, people who choose to pursue librarianship come from the humanities. But is this true, or just based on a bibliophilic stereotype? And how many, if any, people pursuing librarianship come from a design background? Based on data from additional MLIS programs (a mix of iSchools members and non-members), I found very few instances of degrees in art-related fields (5.7%, n=4375); only about 30 of which reflected any sort of formal design education.4

If students aren’t entering programs with design knowledge, then it must fall to the programs to provide it. Therefore, my next step was a field scan of current design-related courses offered in MLIS programs. A preliminary curricular review of the top 20 ALA-accredited master’s level library education programs revealed that none required compulsory coursework in design.5 However, a few notable examples of optional elective courses incorporating aspects of design epistemology have recently emerged, including courses at Simmons College, the University of Maryland, San Jose State University, and the University of Washington. To understand a more holistic picture, I am currently undertaking a field scan compiling and analyzing curricular information from ALA-accredited MLIS program websites and course catalogs. About 50% of these programs are offered by iSchools member institutions, while the other half are not affiliated with the iSchools organization. Although our analysis is currently in progress, preliminary emergent patterns across both types of programs show that design tends to manifest in courses addressing research methods; database development; information management; information systems architecture; human-computer interaction; and web design—all courses that span the breadth of iSchool coverage. Additionally, two library-specific areas have been identified as including design-related content: school media programming and public library programming.

This field scan is the first phase of an Institute of Museum and Library Services (IMLS) National Forum Grant (RE-98-17-0032-17) investigating current incorporations of design thinking, methods, and perspectives in MLIS programs and how design might be increasingly included in these educational experiences. In addition to the field scan, we are also soliciting feedback regarding the interest in and use of design thinking and methods in library practice, and the use of and need for design skills and abilities in library practice from active librarians. The findings from these projects will inform a gathering of educators to be held next spring, in which we will review and discuss the results of the field scan and feedback from practitioners, identify aspects of design education relevant to MLIS education, share professional experiences, and brainstorm curricular approaches. If you are interested in participating in this gathering, please feel free to contact me!

Click to view references 1—5

Dr. Rachel Ivy Clarke

Rachel Ivy Clarke is an assistant professor at the Syracuse University School of Information Studies. Before becoming an academic, she worked as a graphic designer and librarian, (among other things). In addition to her MLIS and iSchool PhD, she holds a BA in creative writing. Clarke was the winner of the 2017 iSchools Doctoral Dissertation Award. For more about her work, click here.


International Degree and Post-Diploma Mobility in Information Science


My master’s thesis deals with the international degree and post-diploma mobility in information science. I explored patterns of the geographical mobility of researchers to find out if in this research field there exists a “brain drain.” Brain drain or brain gain describes the migration of scientists from their home country to another. The results are based on a quantitative dataset of 882 active information science researchers who have been involved in the 2014 to 2016 iConferences. The quantitative part of the study reveals two alarming trends: the American LIS researchers mostly never left their continent and might lack international exposure. On the other hand, researchers from Asia and Europe show a high rate of mobility towards North America. In particular the next generation of IS researchers receives its education in North America. 94.3 % of all Ph.D. students in the sample currently live in the US and may never return to their home countries.

Graphic: Modelling of factors

In the second part of my thesis I interviewed 16 information scientists from the quantitative sample to figure out the reasons for researchers and students to stay, come to or leave Europe. Family is an important personal factor that influences staying or leaving, just as getting a job or a funded Ph.D. position seems to be important for curricular and financial reasons. In another part of the interviews I asked how the information behavior of scholars and students change through international mobility. The awareness of changes in one’s own skills, when it comes to information seeking in work-related matters, is low. Mostly the researchers described the changes in their environment instead. The scholars said that their peers have more influence on their own research than the country they are working in.

Graphic: All Ph.D. Students

For some research topics mobility is not required, either because the topics are national and could be observed locally, or the working materials are easy to access no matter where the researcher is. Through the digitalization of knowledge, the second scenario largely depends on the access given by an institution. Based on the interview data I created a model of the environment providing this access to information and others factors. Infrastructure, research culture and financial resources are the three parameters influencing the researchers work directly. This triangle is shaped by the political and economic conditions of a country.

One important condition for Information science covered by this model under research culture is that English became the lingua franca our research field. If the lingua franca in information science remains English, and the English-speaking countries have a perceptibly more attractive research environment, students and scholars will move there. And their coming back cannot be controlled, for that mobility and migration are too highly subjective.

Brain drain has many negative connotations. It became a buzzword in economic and migration research to stir up the fear of losing elite researchers to competitors. If the European Research Area offers multilingual information research, it could be a strength. Especially with more support for the personal life of researchers and their families, and more funded PhD positions to tie students and scholars to the continent. The longer young people stay in a country, the more likely it is that they connect with the local research community and do not lose contact with it later. Through this contact, the loss of the researchers is not serious because the circulation of knowledge does not dry up that quickly, as the diaspora research shows.

Click here to access Hilebrand’s paper on this subject.
View Hilebrand’s master’s thesis.

Vera Hillebrand holds a BA and MA in LIS from the Berlin School of Library and Information science. She is now research associate for the research group of Information Behaviour.