Emotions Trump Facts: The Role of Emotions in on Social Media: A Literature Review

Emotions are an inseparable part of how people use social media. While a more cognitive view on social media has initially dominated the research looking into areas such as knowledge sharing, the topic of emotions and their role on social media is gaining increasing interest. As is typical to an emerging field, there is no synthesized view on what has been discovered so far and - more importantly - what has not been. This paper provides an overview of research regarding expressing emotions on social media and their impact, and makes recommendations for future research in the area. Considering differentiated emotion instead of measuring positive or negative sentiment, drawing from theories on emotion, and distinguishing between sentiment and opinion could provide valuable insights in the field

Using Twitter to Predict the Stock Market - Where is the Mood Effect?

Behavioral finance researchers have shown that the stock market can be driven by emotions of market participants. In a number of recent studies mood levels have been extracted from Social Media applications in order to predict stock returns. The paper tries to replicate these findings by measuring the mood states on Twitter. The sample consists of roughly 100 million tweets that were published in Germany between January, 2011 and November, 2013. In a first analysis, a significant relationship between aggregate Twitter mood states and the stock market is not found. However, further analyses also consider mood contagion by integrating the number of Twitter followers into the analysis. The results show that it is necessary to take into account the spread of mood states among Internet users. Based on the results in the training period, a trading strategy for the German stock market is created. The portfolio increases by up to 36 % within a six-month period after the consideration of transaction costs

Pass it on: towards a political economy of propensity

The paper argues that the work of Gabriel Tarde on imitation provides a fertile means of understanding how capitalism is forging a new affective technology which conforms to a logic of propensity rather than to means-end reasoning. This it does by drawing together a biological understanding of semiconscious cognition with various practical geometric arts so as to re-stage the world as a series of susceptible situations which can be ridden rather than rigidly controlled. The paper examines the advent of technologies which attend to the variable geometry of so-called animal spirits in the realm of business and then, using Tarde's work as a springboard, considers some alternative means of understanding imitative rays which have less instrumental undertones. The paper is an illustration of the way in which biology and culture have increasingly become intertwined

Analysing the connectivity and communication of suicidal users on Twitter

In this paper we aim to understand the connectivity and communication characteristics of Twitter users who post content subsequently classified by human annotators as containing possible suicidal intent or thinking, commonly referred to as suicidal ideation. We achieve this understanding by analysing the characteristics of their social networks. Starting from a set of human annotated Tweets we retrieved the authors’ followers and friends lists, and identified users who retweeted the suicidal content. We subsequently built the social network graphs. Our results show a high degree of reciprocal connectivity between the authors of suicidal content when compared to other studies of Twitter users, suggesting a tightly-coupled virtual community. In addition, an analysis of the retweet graph has identified bridge nodes and hub nodes connecting users posting suicidal ideation with users who were not, thus suggesting a potential for information cascade and risk of a possible contagion effect. This is particularly emphasised by considering the combined graph merging friendship and retweeting links

Using Social Media Websites to Support Scenario-Based Design of Assistive Technology

Indiana University-Purdue University Indianapolis (IUPUI)Having representative users, who have the targeted disability, in accessibility studies is vital to the validity of research findings. Although it is a widely accepted tenet in the HCI community, many barriers and difficulties make it very resource-demanding for accessibility researchers to recruit representative users. As a result, researchers recruit non-representative users, who do not have the targeted disability, instead of representative users in accessibility studies. Although such an approach has been widely justified, evidence showed that findings derived from non-representative users could be biased and even misleading. To address this problem, researchers have come up with different solutions such as building pools of users to recruit from. But still, the data is not widely available and needs a lot of effort and resource to build and maintain. On the other hand, online social media websites have become popular in the last decade. Many online communities have emerged that allow online users to discuss health-related subjects, exchange useful information, or provide emotional support. A large amount of data accumulated in such online communities have gained attention from researchers in the healthcare domain. And many researches have been done based on data from social media websites to better understand health problems to improve the wellbeing of people. Despite the increasing popularity, the value of data from social media websites for accessibility research remains untapped. Hence, my work aims to create methods that could extract valuable information from data collected on social media websites for accessibility practitioners to support their design process. First, I investigate methods that enable researchers to effectively collect representative data from social media websites. More specifically, I look into machine learning approaches that could allow researchers to automatically identify online users who have disabilities (representative users). Second, I investigate methods that could extract useful information from user-generated free-text using techniques drawn from the information extraction domain. Last, I explore how such information should be visualized and presented for designers to support the scenario-based design process in accessibility studies

Social media mental health analysis framework through applied computational approaches

Studies have shown that mental illness burdens not only public health and productivity but also established market economies throughout the world. However, mental disorders are difficult to diagnose and monitor through traditional methods, which heavily rely on interviews, questionnaires and surveys, resulting in high under-diagnosis and under-treatment rates. The increasing use of online social media, such as Facebook and Twitter, is now a common part of people’s everyday life. The continuous and real-time user-generated content often reflects feelings, opinions, social status and behaviours of individuals, creating an unprecedented wealth of person-specific information. With advances in data science, social media has already been increasingly employed in population health monitoring and more recently mental health applications to understand mental disorders as well as to develop online screening and intervention tools. However, existing research efforts are still in their infancy, primarily aimed at highlighting the potential of employing social media in mental health research. The majority of work is developed on ad hoc datasets and lacks a systematic research pipeline. [Continues.]</div

Law and Ethics of Experiments on Social Media Users

If you were on Facebook in January 2012, there is a chance that it tried to make you sad. If you were on OkCupid, there is a chance that it tried to match you up with someone incompatible. These were social psychology experiments: Facebook and OkCupid systematically manipulated people\u27s environments to test their reactions. Academics doing similar experiments in a university setting would typically need to obtain informed consent from participants and approval from an Institutional Review Board (IRB). But Facebook and OkCupid, and the academics working with Facebook, had neither. This, I believe, is a problem. These experiments offer us a moment for reflection, a chance to discuss the law and ethics of experiments on social media users. In this essay, I will consider social media research through the prism of the Facebook and OkCupid experiments. I will focus on three questions: (1) When do social media experiments constitute research involving people? (2) What does it take to obtain the informed consent of users? (3) What institutions are responsible for reviewing such experiments? Part I offers an initial review of the Facebook and OkCupid research projects. Part II -- the bulk of the essay -- takes up these questions under current law. Part III considers the broader question of what the rules for regulating social media research ought to be. The most immediately pressing priority is to prevent the unraveling of the existing ethical framework through IRB laundering, in which a regulated institution outsources enough work to an unregulated one to evade IRB review and informed consent. Looking further ahead, I offer some tentative thoughts on the scope of coverage, informed consent, and oversight for social media experiments. Finally, the conclusion reflects on how we should think about consent in this setting