DYNAMICS OF IDENTITY THREATS IN ONLINE SOCIAL NETWORKS: MODELLING INDIVIDUAL AND ORGANIZATIONAL PERSPECTIVES

This dissertation examines the identity threats perceived by individuals and organizations in Online Social Networks (OSNs). The research constitutes two major studies. Using the concepts of Value Focused Thinking and the related methodology of Multiple Objectives Decision Analysis, the first research study develops the qualitative and quantitative value models to explain the social identity threats perceived by individuals in Online Social Networks. The qualitative value model defines value hierarchy i.e. the fundamental objectives to prevent social identity threats and taxonomy of user responses, referred to as Social Identity Protection Responses (SIPR), to avert the social identity threats. The quantitative value model describes the utility of the current social networking sites and SIPR to achieve the fundamental objectives for averting social identity threats in OSNs. The second research study examines the threats to the external identity of organizations i.e. Information Security Reputation (ISR) in the aftermath of a data breach. The threat analysis is undertaken by examining the discourses related to the data breach at Home Depot and JPMorgan Chase in the popular microblogging website, Twitter, to identify: 1) the dimensions of information security discussed in the Twitter postings; 2) the attribution of data breach responsibility and the related sentiments expressed in the Twitter postings; and 3) the subsequent diffusion of the tweets that threaten organizational reputation

Essays in Environmental Economics

This dissertation consists of three essays in the field of environmental economics. The first chapter provides the first causal evidence that hostile activities online lead to physical violence. Given the recently documented relationship between pollution and social media, I exploit exogenous variation in local air quality as the first step to instrument for online aggression. In an event study setting, I find volatile organic compounds (VOCs) increase by 7% when refineries experience unexpected production outages. Together with higher air pollution, I find more aggressive behaviors both online and offline, as well as worse health outcomes near refineries. A one standard deviation increase in surrounding VOCs leads to 0.16 more hate crimes against Black people and 0.23 more hospital visits per thousand people each day. Second, I consider how emotional contagion spreads through social networks. On days with pollution spikes, surrounding areas see 30% more offensive and racist tweets and 12% more crimes; those geographically distant but socially networked regions also see offensive and racist tweets increase by 3% and more crimes by 4.5%. Nationally, overlooking spillovers would underestimate crime effects of pollution by 24%. My findings highlight the consequences of social media hostility and contribute to the public debate on cyberspace regulation. The second chapter, which is coauthored with Andrew Wilson, analyzes the relationship between weather and railway accidents. Rail thermal expansion and contraction are key considerations in rail design and construction; rail operators and rolling stock may likewise exhibit vulnerability to temperature changes. We quantify the sizes of these effects by leveraging a comprehensive dataset of railway malfunctions in the United States spanning 1997-2019. We find that both heat and cold cause elevated rates of railway malfunctions, with relatively larger increases in the number of incidents leading to a casualty as well as the number of injuries and deaths resulting from these incidents. We find that exposure to daily temperatures averaging over 30°C (86°F) leads to a 16% increase in the number of rail malfunctions, a 13% increase in the number of incidents leading to a casualty, and 18% and 36% increases injuries and deaths-effects net of any operational adjustments made to mitigate these effects. Further, while we also find that warmer locations exhibit a weaker relationship between heat and railway malfunctions, we find no evidence that companies are learning, year-over-year, how to reduce accidents. Finally, we note that effects of heat are strongest for derailments (versus other types of malfunctions) and freight trains (versus passenger trains). Our findings highlight the vulnerability of the railway system to the climate. The number of injuries and deaths associated with weather exposure-especially in comparison to operators' reported private costs of equipment failure-suggests a role for enhanced rail safety regulations and adaptation funding to protect critical heat-exposed infrastructure. The third chapter, which is a joint work with Douglas Almond and Muye Ru, explores the impact of federal policy rollback on methane leakage. Improvements in satellite measurement enable independent assessment of regulatory and climate policy. In August 2020, the Trump Administration lifted Obama-era requirements that oil and gas firms detect and repair methane leaks. We merge geo-identified data from the European TROPOMI (satellite instrument) to the specific locations of the US oil and gas infrastructure. Using a difference-in-differences design, we find a prompt increase in US methane emissions following the summer 2020 rollback. The number of high-methane emission events from the oil and gas sector more than doubled after the rollback relative to the coal sector, which did not experience the same regulatory rollback. While the oil and gas industry claims it faces a persistent, profit-making incentive to stem natural gas leaks and emissions, we find a large and nimble response by industry to changes in federal policy. Public policies that reduce methane externalities are critical given that global methane concentrations are rising at an increasing rate

Tugging at the heartstrings? : examining discrete emotion in nonprofit Twitter messages and its effect on pass along behavior

The rise of social media has provided organizations with new tools for interacting with customers and building relationships and have created an ideal place to foster and nurture emotional connections. Nonprofit organizations now strongly rely on the sharing of their social media messages to deliver important information, build community, and mobilize supporters (Lovejoy & Saxton, 2012). However, research regarding the extent to which nonprofits use emotions in social media communications is quite limited. The inclusion of emotional content is important in message virality, however, only very limited research exists on the types of emotional content that is included in nonprofit Twitter messages. Therefore, relevant data and descriptive frameworks are essential to helping us understand how nonprofit organizations are using microblogging sites to engage with their target audiences. This research takes a first step in this regard to investigate the effect that emotion can have on pass along behavior. Using Social Sharing of Emotion (Rime Finkenauer, Luminet, Zech, and Philippot, 1998, Rime 2009) as the theoretical foundation, this dissertation specifically examines nonprofit usage of discrete emotion and its effect on pass along behavior. This research found that nonprofits are using emotional content in their Twitter messages to communicate with their public. Specifically, nonprofits are using the focal eight discrete emotions as follows: Trust (33.3%), anticipation (30.4), joy (27.9%), fear (17.2), surprise (13.8%), sadness (13.6%), anger (12.2%), and disgust (7.1%). Additionally, results indicate that using emotive content in nonprofit Twitter messages can influence pass along behavior. Specifically, results indicate that nonprofit messages that utilized fear, sadness, surprise, or trust positively influenced pass along behavior. In contrast, use of anticipation-related words had a negative impact of pass along behavior, and thus while it is currently the second most utilized emotion it should be used cautiously. Therefore, nonprofits can now better employ emotive content to extend the reach of the messages to see their messages spread further.Advertisin

UNDERSTANDING PARACRISIS COMMUNICATION: TOWARDS DEVELOPING A FRAMEWORK OF PARACRISIS TYPOLOGY AND ORGANIZATIONAL RESPONSE STRATEGIES

For the past few years, both academic and trade publications have repeatedly found that “social media crises” were at the core of organization fears. This dissertation argues that one of most important reasons for such fear is the prevalent use of the term “social media crisis” to refer to both crises and risks emerging from social media, which obscures the differences between risks and crises and among various types of risks that might require different organizational responses. To address this problem, Coombs and Holladay proposed the term “paracrisis” to describe more accurately crisis risks as socially constructed in social media. They also developed conceptual work on classifying paracrisis clusters and response strategies. However, extant crisis communication research and practice has largely failed to incorporate this concept. The first focus of this dissertation is thus to build on their work to refine and expand the framework of paracrisis clusters and response strategies with empirical data by collecting and 143 paracrisis cases occurring during January 2014 to December 2017 (Study 1). The other focus is to examine how might a paracrisis evolve on and off social media to gain more sophisticated understanding on how the publics communicatively construct a paracrisis and how a paracrisis differs from a full-blown crisis. To serve this focus, a big data case study using mainly computational methods has being conducted to analyze 210, 892 tweets, along with offline news coverage (Study 2). As such, this dissertation contributes to the severely understudied paracrisis communication research by identifying typologies on paracrisis types and response strategies and gaining initial understanding to paracrisis communication processes as socially constructed on and off social media. The research findings also offer practical suggestions for social media practitioners to diagnose and strategically respond to paracrises

CLINICAL AND SOCIAL PATHWAYS TO CARE: A COMPUTATIONAL EXAMINATION OF SOCIAL MEDIA FOR MENTAL HEALTH CARE

In the last decade, powered by connectivity to large social networks and advances in collecting and analyzing digital traces of individuals from social media platforms, researchers have gleaned rich insights into individuals’ and populations’ mental health states and experiences, including their moods, emotions, social interactions, language, and communication patterns. Using these inferences, researchers have been able to study support-seeking behaviors, distinguishing patterns, risk markers, and diagnosis states for mental illnesses from social media data, promising a fundamental change in mental health care. What we need next in this line of work is for data and algorithms based on social media to be contextualized in people’s pathways to mental health care. However, there are several challenges and unanswered questions that present hurdles. First, gaps exist in the psychometric validity of social media based measurements of behaviors and the utility of these inferences in predicting clinical outcomes in patient populations. Second, if social media can act as an intervention platform, outside of discrete events, a holistic understanding of its role in people’s lives along the course of a mental illness is crucial. Lastly, several questions remain around the ethical implications of research practices in engaging with a vulnerable population subject to this research. This thesis charts out empirical and critical understandings and develops novel computational techniques to ethically and holistically examine how social media can be employed to support mental health care. Focusing on schizophrenia, one of the most debilitating and stigmatizing of mental illnesses, this thesis contributes a deeper understanding on pathways to care via social media along three themes: 1) prediction of clinical mental health states from social media data to support clinical interventions, 2) understanding online self-disclosure and social support as pathways to social care, and 3) the intersection of social and clinical pathways to care along the course of mental illness. In doing so, this work combines theories from social psychology, computer-mediated communication, and clinical literature with machine learning, statistical modeling, and natural language analysis methods applied on large-scale behavioral data from social media platforms. Together, this work contributes novel methodologies and human-centered algorithmic design frameworks to understand the efficacy of social media as a mental health intervention platform, informing clinicians, researchers, and designers who engage in developing and deploying interventions for mental health and well-being.Ph.D

The cause, development and outcome of word-of-mouth marketing: with particular reference to WOM volume, valence and the modeling of viral marketing

Viral marketing is a form of online word-of-mouth (WOM) communication in which individuals are encouraged to pass on promotional messages through social websites. With the growing popularity of online social websites, viral marketing has increasingly garnered attention of marketers and marketing researchers alike. The two most important WOM attributes highlighted in the extant literature are volume and valence. This thesis looked into the cause, development and outcome of WOM marketing and provided computational models for forecasting the development of WOM volume and valence of viral marketing in social websites. With the data extracted from large-scale web-crawling activities, through a series of computer simulation experiments comparable to social websites, the author developed models to predict WOM volume and valence in viral marketing. The model for predicting WOM volume in viral marketing used theories of network topologies. The model for predicting WOM valence in viral marketing used an artificial neural network model. The author discussed the insights from the findings and suggested viral marketing strategies to optimize the performance of WOM volume and valence in social websites. A key contribution of this thesis is the new approaches of modeling and data collection for WOM volume and valance forecasting in viral marketing

Software and the struggle to signify: theories, tools and techniques for reading Twitter- enabled communication during the 2011 UK Riots

This thesis analyses communication on the micro-blogging service Twitter during the 2011 UK riots. It examines the complex constructive relationship between software and collective meaning-making during a period of acute social crisis and asks whether Twitter’s software-structures facilitated productive, democratic discourse. While politicians rushed to impose ‘Victorian’ condemnation on the moral failings of rioters and their families (Bridges 2012) the broadcast and print media delivered commentary that was reductive, politicised and polemical (Kelsey 2012). These concerns, combined with an absence of rigorous, critical oversight, suggest a failing of the public sphere. While some theorists have argued that Internet media should be capable of fulfilling a normative-democratic role (Kellner 2004), the temporality of Internet-enabled communication may undermine democratic expectations, because the rapidity of information flow stresses the deliberative period (Barber 2006, Hassan 2012, Buchstein 2002). To examine this issue, the conceptual framework identifies several ‘logics’ by which the software-constructed temporality of communication should interact with the normative requirements of deliberative exchange. These logics frame the development of an empirical methodology. Analysis of thematic content, deliberative potential and the constructive influence of Twitter time-space in the riot public produces the following key findings. 1. The most dominant thematic concerns reflect closely discourse in the wider mediasphere. Twitter users strive to explain the riots, seeking and analysing socio-structural causes 2. There is clear evidence of a relationship between software-structures and discourse. Twitter’s hashtag syntax supports thematically and deliberatively discreet discourse streams. 3. Deliberative tweets concentrate in the #UKRiots stream, suggesting that there may be discreet ‘hashtag cultures’ on Twitter – communities that are shaped by (or themselves shape) structural identifiers and are committed to a certain type of discourse. 4. While such hashtag cultures may suggest coordination, Twitter permits different ‘langues' that discourage deliberation. Analysis across the structural layers finds little evidence of ideal speech conditions. 5. The majority of tweets contain links to external media, and this has implications both for the deliberative potential of tweets. The logic of hyperlinking ‘defers’ meaning in complex ways. Locating and ‘restricting’ meaning is thus extremely difficult. 6. There is some evidence that the temporality of hashtag streams may reveal something about the dynamics of discourse coordination. As stream density increases, communicative reasoning may become more difficult. These findings suggest some important conclusions about the democratic potential of Twitter discourse and some priorities for future research. Principal among these is a call for greater dialogue between the computing, statistical and social sciences. Barber, Benjamin R. 2006. "How democratic are the new telecommunication technologies?" Second Conference on the Internet, law and politics: analysis and prospective study, Barcelona, Open University of Catalonia (UOC). Bridges, Lee. 2012. "Four days in August: the UK riots." Race & Class 54 (1):1-12. Buchstein, Hubertus. 2002. "Bytes that bite: the Internet and deliberative democracy." Constellations 4 (2):248-263. Hassan, Robert. 2012. Not ready for democracy: social networking and the power of the people. The revolts of 2011 in a temporalized context. Arab Media & Society 15. Accessed 10 October 2014. Kellner, Douglas. 2004. "9/11, spectacles of terror, and media manipulation: A critique of Jihadist and Bush media politics." Critical Discourse Studies 1 (1):41-64. Kelsey, Darren. 2012. "Defining the ‘sick society’: Discourses of class and morality in British right- wing newspapers during the 2011 England riots." Capital & Class 39 (2):243-264