CCE Theses and Dissertations

Date of Award

2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

College of Computing and Engineering

Advisor

Ling Wang

Committee Member

Inkyoung Hur

Committee Member

Sun Junping

Abstract

Social media networking sites (SMNS) have become a popular communications medium where users share information, knowledge, and persuasion. In less than two decades, social media's (SM) dominance as a communication medium can't be disputed, for good or evil. Combined with the newly found immediacy and pervasiveness, these SM applications' persuasive power are useful weapons for organizations, angry customers, employees, actors, and activists bent on attacking or hacking other individuals, institutions, or systems. Consequently, SM has become the preferred default mechanism of news sources; however, users are unsure if the information gathered is true or false. According to the literature, SMNS generates large amounts of fake news or disinformation. The rapid proliferation of disinformation, information disseminated with the intent to harm, through SMNS has dramatically influenced and reduced people's trust in the story and hints at hand. Disinformation has caused data breaches and many injured individuals and organizations, resulting in a lack of confidence in SMNS. While irrefutable that SMNS has become the new news outlet, trust remains the foundation of all communication. Since SM has changed the communication process, it is perceived as the most dangerous information dissemination vehicle known to society. Unfortunately, no one is safe from its lethality. Users must approach their usage with extreme care by understanding the technical capabilities and increasing their competence in detecting disinformation campaigns' powerful influence. The continuous spread of disinformation has caused the credibility and trust of behemoths like Facebook, Twitter, and Instagram, to be significantly affected. Since trust is an essential factor in SMNS, mistrust hinders users' abilities to make informed decisions. Research suggests that people make decisions based on the available information; therefore, it can be deduced that the decision-making process of SMNS users has been forever altered. Consequently, monitoring the spread of disinformation has become a front-burner priority for the government and society. By examining the effect of trust moderated by disinformation, this study aimed to investigate the factors that affect SMNS users' decision-making behaviors. Factors influencing trust were also examined using the Conformity Group Norm Theory (CGNT) and Self Concept Theory (SCT). A theoretical model was created, and there were seven constructs; decision-making (DM), trust (TR), and the trust influencing factors: identification (ID), compliance (CP), internalization (IN), agency (AG), and community (CM). The theoretical model tested was based on the linear directional relationship of trust and decision making moderated by disinformation.

This research tested three social media networking sites, Facebook, Twitter, and Instagram, with disinformation empirically. This quantitative study employed a role-play scenario web survey methodology and adopted a two-step Pearson r correlation coefficient procedure for data analysis. Before collecting data, an expert panel reviewed, and pilot tested the survey. The expert review recommended changes to the wording, length, and formatting of the instrument, allowing the pilot test to be easily tested by participants. The web-based scenario survey was designed with a 5- point Likert scale and distributed to SMNS users through Qualtrics XM to gather data on their decision-making process.

The data analysis results revealed the moderating effect of disinformation between trust and the decision-making process of SMNS users. The data supported the conformity group norm theory (CGNT) and self-concept theory (SCT) factors. The results indicated that identification (ID), compliance (CP), internalization (IN), agency (AG), and community (CM) influence trust. Since the spread of disinformation through SMNS has much broader implications for democracy and society as a whole, this research's results contribute to the knowledge of SM users' behavior and decision-making processes. This study also contributes to the IS body of knowledge on social cybersecurity and has implications for practitioners and academics. This study offers a model by integrating behavioral and cognitive theories better to understand the directional relationship of trust and decision-making when exposed to disinformation. The model also identifies essential elements that influence SMNS users' trust and engage them in risky cybersecurity behaviors. Furthermore, this study provides evidence of the need for future US social media governance.

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