The purpose of this dissertation was to address the degree to which social media can be utilized as a tool for stakeholder communication by not-for-profit sport organizations. Delimited to national sport organizations, specifically those in a Canadian context, and using a stakeholder theory approach, the project advanced three major research objectives: (1) determine what not-for-profit sport organizations are communicating to their stakeholders via social media, including identifying forces and pressures that impact content and messaging; (2) identify which stakeholders are positioned and advantaged in the social network of not-for-profit sport organizations; and (3) uncover the contextual factors that have enabled the use of social media channels by not-for-profit sport organizations. In order to accomplish these objectives, the dissertation was structured into three interconnected stages parsed into three research articles – each with its own supporting theoretical framework (i.e., institutional theory, network theory, and the contextualist approach to organizational change) – providing findings discussed using a stakeholder perspective. In the first article, the results found social media communication was predominantly used for promoting, reporting, and informing purposes, attributable to the coercive (e.g., funding partners), mimetic (e.g., salient organization routines), and normative (e.g., best practices) pressures at play. In the second article, fans, elite athletes, photographers, competing sport organizations, and local sport clubs were identified as key stakeholders with significant advantage given their position in the social media network of not-for-profit organizations. The final article revealed social media has yet to radically impact the operations of these organizations, highlighting some of the challenges related to social media communication. Cumulatively, the findings illustrate not-for-profit sport organizations can improve upon their current use of social media as a stakeholder communications tool. Through the implementation of a unique social media strategy composed of multiple philosophies, not-for-profit sport organizations could consider the variance in stakeholder groups while incorporating the immediacy and engagement social media requires. In doing so, organizations may create the conditions to satisfy stakeholder expectations and increase organizational capacity simultaneously. Concurrently, the findings represent a basis for future research using organizational theory frameworks to explain new trends and phenomena in the social media and sport domain.

The information ecosystem of social media has resulted in an abundance of opinions on political topics and current events. In order to encourage better discussions, it is important to promote high-quality responses and relegate low-quality ones. We thus focus on automatically analyzing and generating counter-arguments in response to posts on social media with the goal of providing effective responses. This thesis is composed of three parts. In the first part, we conduct an analysis of arguments. Specifically, we first annotate discussions from Reddit for aspects of arguments and then analyze them for their persuasive impact. Then we present approaches to identify the argumentative structure of these discussions and predict the persuasiveness of an argument. We evaluate each component independently using automatic or manual evaluations and show significant improvement in each. In the second part, we leverage our discoveries from our analysis in the process of generating counter-arguments. We develop two approaches in the retrieve-and-edit framework, where we obtain content using methods created during our analysis of arguments, among others, and then modify the content using techniques from natural language generation. In the first approach, we develop an approach to retrieve counter-arguments by annotating a dataset for stance and building models for stance prediction. Then we use our approaches from our analysis of arguments to extract persuasive argumentative content before modifying non-content phrases for coherence. In contrast, in the second approach we create a dataset and models for modifying content -- making semantic edits to a claim to have a contrasting stance. We evaluate our approaches using intrinsic automatic evaluation of our predictive models and an overall human evaluation of our generated output. Finally, in the third part, we discuss the semantic challenges of argumentation that we need to solve in order to make progress in the understanding of arguments. To clarify, we develop new methods for identifying two types of semantic relations -- causality and veracity. For causality, we build a distant-labeled dataset of causal relations using lexical indicators and then we leverage features from those indicators to build predictive models. For veracity, we build new models to retrieve evidence given a claim and predict whether the claim is supported by that evidence. We also develop a new dataset for veracity to illuminate the areas that need progress. We evaluate these approaches using automated and manual techniques and obtain significant improvement over strong baselines. Finally, we apply these techniques to claims in the domain of household electricity consumption, mining claims using our methods for causal relations and then verifying their truthfulness.

Social media presents new possibilities of creating knowledge that would not have been possible using other computer-mediated forms. Social media enables enrichment of organisations’ knowledge resources with the extracted insights; however, what is not certain is the factors that are at play when taking a decision to consider social media data as the source of insight that will translate into valuable knowledge that organisations may benefit from. The purpose of this study is to investigate how organisations integrate social media into their knowledge base. The dynamic capabilities and organisational resilience in turbulent environments framework was used as a lens to look into how organisations integrate social media into their knowledge base. A Systematic Literature Review (SLR) was performed to identify, evaluate and interpret all the relevant material or primary studies that are available to answer the research question. Furthermore, an empirical investigation was conducted through the use of interviews and questionnaires. The contribution of the current study to the body of knowledge is twofold. Firstly, synthesis of the existing literature on the uses of social media and knowledge management as well as the evaluation of the model resulted in a revised dynamic capabilities model (DCF) where three capabilities were added, namely validating capability due to questionable SM data quality, crisis management capability for safeguarding the organisations’ reputation, and innovating capability to stay ahead of the fiercely competitive dynamic environment. Secondly, this study produced a significant number of factors that both the literature and the research participants considered key to the implementation of the proposed model. These factors can be categorised into people, processes and technology aspects. The study is significant in the sense that 1) the research findings should be of interest to organisations that are open to innovation and therefore can be used as yardsticks for decision-making; 2) the emergence of the crisis management capability is a major contribution to the body of knowledge as it highlights the importance of proactivity and alertness to responding to conversations of the organisations’ audiences and avoiding the social media backlash suffered by organisations. As the study focused on only one case study, it serves a basis for further research in different sectors of the business with the aim of validating the generality of the proposed model. / Dissertation (MCom)--University of Pretoria, 2020. / Informatics / MCom / Unrestricted

A thesis submitted to the Faculty of Arts in fulfilment of the requirements for the degree of Masters in the Department of Communication Science at the University of Zululand, South Africa, 2012. / Social media participation has spiraled exponentially and has transformed the way in which we communicate. It has opened up a new window which can maximise teaching and learning opportunities in the educational sector. However there are numerous challenges that public schools face when it comes to introducing and implementing technology but there is a need to overcome these barriers to develop and prepare educators and students at public schools for the 21st century. This thesis examines the relevance of social media in public schools. The first part of the study reviews literature on electronic communication, technology and its impact on society and education, challenges faced in educational technology, social media and programmes used in South African schools, Department of Education policies and procedures. Subsequent chapters describe the construction of a survey instrument employed to measure and evaluate the relevance of social media at public schools. The main tool for collecting data was the questionnaire and semi-structured interviews. A questionnaire provided appropriate information required for the research, as questions were asked to learners, educators and personnel from schools in Richards Bay and surrounding areas. Data analysis included using Moonstats to codify the data and graphs were imported to Microsoft Excel which was used for interpretation.Penultimate chapters blend the insights gained from the literature review to interpret the results obtained through the research methodology and to draw up recommendations and conclusions in the context of the relevance of social media in public schools.

A research report submitted in partial fulfilment of the requirement for the degree of Master of Arts to the Faculty of Humanities, University of the Witwatersrand, 2019 / Many local governments around the world have adopted Twitter as a tool to enable two-way communication with its citizens. Academics in the fields of Developmental Communication, Public Administration and Information and Communications Technologies (ICT) have theorised that social media platforms have the ability to enhance the delivery of services by local governments (Guillamón, et al: 2016; Kavanaugh et al: 2012; Perlman: 2012). Based on this theory, the aim of this study is to determine how the Johannesburg Road Agency, a local government entity of the City of Johannesburg in South Africa, used its Twitter account as a tool to communicate with its citizens about service delivery relevant to the entity’s scope of services. For the purpose of this study the researcher used a traditional case study research approach to illustrate how the JRA uses its Twitter account to engage in two-way participatory communication with its citizens about the services it must provide. The data for the case study was collected through content analysis of policy documents, and interviews. The study’s participants, namely the staff from the JRA’s Customer Relations Management (CRM) department, were requested to provide information through these interviews and policy documents. The study found that the JRA uses strategies, policies, protocols and plans to manage its Twitter account with staff that is trained in customer relations management. The researcher argues clientelism is practised at the JRA as the entity’s policy documents and staff members identify its citizens as mere customers paying for a service and not citizens of a democracy with definitive rights. The study further explored whether the citizens of Johannesburg, that use this method of communication with the JRA, find it useful. The majority of participating citizens have expressed that they perceive this method of communication with the JRA to be useful, however, the researcher argues that this method cannot be seen as an appropriate method due to the internet access constraints that the citizens in the City of Johannesburg experience, which prevents the majority of citizens from having access to Twitter as a communication tool. The interviewed staff argued that communicating with citizens on Twitter, a public platform, makes them feel more accountable and makes the process more transparent, while admitting that in some instances they have to lie to citizens when there are problems experienced. Therefore, the researcher concludes that the JRA has not fully utilised the opportunities that Twitter has to offer to realise participatory communication between the public service providers and citizens. / NG (2020)

The number of social media platforms (SMP hereinafter) is ever-increasing, and all of these platforms compete for more attention and content. The global social media market is expected to grow to $223.11 billion in 2022 (Social Media Global Market Report, 2022). In an era characterized by the meteoric rise and evolution of Social Media Platforms (SMPs), understanding the interplay between platform features and user behaviors is both critical and complex. In this dissertation, we aim to elucidate the relationship between SMPs and society, with the ultimate objective of fostering a healthier social media ecosystem. This dissertation is comprised of two incisive essays, both of which are underpinned by robust theoretical frameworks. The first essay adopts an expansive purview of the SMP ecosystem. Grounded in Uses and Gratifications Theory and media studies, it establishes a user typology based on the previous typologies and examines the interaction between user motives, SMP scores, and SMP features. Employing the Analytic Hierarchy Process, a sophisticated decision-making tool, the study quantifies utility-driven choices across platforms. A notable revelation is the heterogeneity in user reliance on SMP features, contingent upon their underlying motives. This essay offers critical insights into the multifaceted nature of SMP utilization. The second essay focuses specifically on Reddit's ChangeMyView community, an exemplar of constructive discourse in the SMP environment. It constructs a theoretical model premised on the Elaboration Likelihood Model and the concept of pre-suasion, and utilizes a mixed-methods approach to explore the persuasive strategies using Content Analysis. We also utilize ChatGPT in the Content Analysis to corroborate our inferences. The findings confirm our theorization about the role of the Delta reward system in fostering reflective engagement with content, which leads to informed opinion formation. Collectively, with these essays, we aim to provide extensive insights into the dynamic interplay between SMPs and users. Both essays hold significant implications for research community, SMP decision-makers, organizations that use SMPs, and a broader audience interested in optimizing their social media repertoire. Through a theory-driven and empirical lens, employing several epistemologies, this dissertation provides a holistic depiction of the SMP ecosystem. / Doctor of Philosophy / The landscape of social media is constantly evolving with an ever-growing number of platforms vying for user attention. In this dissertation, we aim to analyze the relationship between social media platforms and their users, seeking ways to foster a healthier and more constructive social media environment. This dissertation is structured into two distinct yet interconnected essays. In the first essay, we look at the broader ecosystem of social media platforms. It categorizes users based on their motivations for using social media, such as seeking information or connecting with others. We examine how different features of social media platforms cater to these diverse motivations. To accomplish this, we employ a method known as the Analytic Hierarchy Process, which is a decision-making tool used to measure and analyze choices. The key insight from this essay is the diversity in how users interact with social media features, and how this interaction is influenced by their underlying motivations. In the second essay, we take a closer look at a specific community on Reddit called ChangeMyView. This community is unique as it encourages users to engage in thoughtful and reasoned debates. In this essay, we develop a theoretical model to understand the mechanisms through which information is processed and opinions are changed within this community with a strong focus on Delta system, a feature that rewards users for successfully changing someone's opinion through challenging their view and pointing the flaws in their thinking. Collectively, the dissertation provides an in-depth understanding of the dynamic relationship between social media platforms and users. It does so through rigorous analysis underpinned by theoretical frameworks. This research is not only academically significant but also has practical implications. It provides valuable insights for decision-makers to improve social media platforms, aids organizations in understanding how best to engage with social media, and informs users on optimizing their social media interactions. In essence, this dissertation serves as a comprehensive analysis that bridges the gap between the ever-evolving features of social media platforms and the multifaceted behaviors of their users.

With the online presence of more than half the world population, social networks and social media plays a very important role in the lives of individuals as well as businesses alike. While there are advantages to using these online platforms, there as also downsides that one should be wary about. We focus on analyzing the information or the content that spreads on online platforms. Text summarization is a crucial task that helps in condensing an enormous amount of social media content. While there are multiple approaches to text summarization, the development of an automatic metric to evaluate the generated summaries remains an open problem in text summarization. We propose a novel evaluation metric, Sentence Pair EmbEDdings (SPEED) Score, for text summarization which is based on semantic similarity between sentence pairs. Our proposed evaluation metric shows an impressive performance in evaluating both abstractive and extractive summarization models and is faster than the current state-of-the-art metrics. In this research, we also put forward a multi-source transfer learning approach using models pre-trained on large-scale datasets to detect inappropriate social media content in universal language (English) and code-mixed environments. Here, sentiment analysis is the process of identifying the emotion associated with these social media texts. The presence of sarcasm in texts is the main hindrance in the performance of sentiment analysis. Inherent ambiguity in sarcastic expressions, make sarcasm detection very difficult. In this work, we focus on detecting sarcasm in textual conversations from various social networking platforms and online media. To this end, we develop an interpretable deep learning model that uses attention to identify crucial sarcastic cue words from the input.

With the growing use of Online social media (OSM), users are observing a substantial amount of information in their social feeds. Moreover, people often use multiple OSM platforms because of each platform's unique features. Because of the huge volume of information present in social feeds, it restricts a user's ability to process the relevant information since the most important information may be overwhelmed by unimportant information. For information to diffuse in OSM, the receiver's attention is the most important condition. Cognition plays an important role in determining a user's attention/responsiveness. If OSM users receive the information above their cognition limits and become less responsive, they are in an information-overloaded state. I believe there are several factors that can lead OSM users to be in an information overload state. The main purpose of this study is to explore some of the factors that can affect the ability of OSM users to respond to information while they are overloaded. In this study, I explore two major factors: (1) Influence Gradient i.e., the differences in the magnitude of influence exerted and influence experienced by each OSM user who is active in either single or multi-platform OSM, and (2) Emotion Contagion i.e., the effects on users' response capacity due to the emotional stimuli in the content of social media messages delivered from the influencers to their receivers. Experiments are designed using Information Overload Model (IOM), which quantifies an individual's current information processing capacity (IPC), and the Multi-Action Cascade Model (MACM) which simulates the information diffusion on social media. IOM is implemented into the agents of the MACM model to simulate information diffusion phenomena. They are incorporated with memory, and their IPC can be quantified along with the flow of information into the network such as the amount of information they stored to respond, new messages they received from their influencers, and the information overload they experience. Transfer entropy is used to quantify peer influence between the users in single or multi-platform OSM. I use empirical data from GitHub, Twitter, and YouTube. For GitHub, I use repositories related to the cryptocurrency community. Twitter and YouTube data is extracted from profiles engaged in narratives related to China-Pakistan economic corridor under one belt one road initiative. For the emotion contagion experiment, I use Twitter data on Venezuela's election dispute in early 2019. From this research work, I find evidence that negative influence gradients lower the IPC of OSM users active in both single and multi-platform. This shows that users who are influenced more than they can exert their influence on others are the ones to be overloaded. While the users exerting more influence on others can function at full capacity. I found that there exists emotional contagion from the influencers to receivers and un-overloaded users are affected by such contagion. Overloaded users are not supposed to be affected by emotional contagion. Interestingly, I found that overloaded users are still affected by negative emotions and chose to respond to them and ignore messages with positive emotions.

Typically, online social influence is analyzed using a single metric approach. However, social influence is not monolithic; different users exercise different influences in different ways, and influence is correlated with the user and content-specific attributes. One such attribute could be whether the action is an initiation of a new post, a contribution to a post, or a sharing of an existing post. Thus, this dissertation uses this platform-independent action classification and models the influence as multiple entities and examines social networks through the perspective of behavioral influence propagation. Two empirical studies are present in this dissertation. The first study presents a novel method for tracking these influence relationships over time, which we call influence cascades, and presents a visualization technique to understand these cascades better. These influence patterns are investigated within and across online social media platforms using empirical data and comparing to a scale-free network as a null model. Our results show that characteristics of influence cascades and patterns of influence are, in fact, affected by the platform and the community of the users. The second study applies the same framework to re-construct interconnected social networks and explores the significance of cross-platform influence on social media users in the influence process. In particular, we explore the social dynamics of users with a higher number of social influence relationships across platforms, which we call interface users, and those with fewer social influence relationships across platforms, which we call core users. Our results find that interface users are more vulnerable to being influenced and influential than core users. Further, our results show that the interface users who are influenced to do initiation action exert significantly more influence on others than those who are influenced to contribute.

Social networking sites have become popular communication tools to make connections and maintain interpersonal relationships, especially for long-disance romantic relationship. Given the popularity of this new communicative platform, this study aims at updating their pattern in terms of their benefits in maintenance romantic relationships among college students. 133 students were recruited to assess their maintenance behaviors through their uses of computer-mediated communication and some traditional communicative channels as well as their uncertainty level. This results reveal that long-distance romantic relationship partners use computer-mediated communication tools such as texting, direct messaging, Snapchat, and others more frequently than partners in geographically close relationships. In addition, this study finds that relationship maintenance performed on social media sites and face-to-face associate with relationship uncertainty. This study offers a new way to look at social networking sites as the maintenance behaviors for long-distance romantic relationship partners by comparing these new channels with the face-to-face maintenance communication. Such comparisons draw a bigger picture of how the long-distance romantic relationship maintenance operates in this digital age.