Relating Social Media Diffusion, Education Level and Cybersecurity Protection Mechanisms to E-Participation Initiatives: Insights from a Cross-Country Analysis

2023 | Information Systems Frontiers | Citations: 0

Authors: Ahangama, Supunmali

Abstract: Virtual Social Networks (VSN) act as a catalyst for the success of the active pa ... Expand

Abstract: Virtual Social Networks (VSN) act as a catalyst for the success of the active participation of citizens in information sharing, collaboration, and decision making. VSN based e-participation tools allow many-to-many communication and collaboration near real-time with users who might be in geographically dispersed locations. It provides a platform to voice opinions and perspectives and share them with others in new and innovative ways. Cybersecurity is a key area that needs to be considered for the success and continuous use of e-participation systems as it protects user privacy and helps to avoid scams, harassment, and misinformation. The intervening effect of cybersecurity protection mechanisms and citizens’ education level on the relationship between VSN diffusion and e-participation initiatives is explored in the proposed research model presented in this paper. Moreover, this research model is explored for different stages of e-participation (e-information, e-consultation, and e-decision making) and the five dimensions of cybersecurity (legal, technical, organizational, capacity building, and cooperation). The findings indicate that improved VSN usage has increased e-participation (especially in e-consultation and e-decision making) as a result of improved cybersecurity protection and public education, highlighting the varying importance of different cybersecurity protection measures for three stages of e-participation. Thus, considering the recent problems like platform manipulation, misinformation and data breaches associated with the use of VSN for e-participation, this study emphasizes the importance of regulations, policies, partnerships, technical frameworks, and research to ensure cybersecurity, as well as the importance of education to enable the public to interact productively in e-participation activities. This study is performed using publicly available data from 115 countries and the research model is developed, drawing theoretical basis from the Protection Motivation Theory, Structuration Theory, and Endogenous Growth Theory. This paper recognizes the theoretical and practical implications, and limitations while recommending future research directions. Collapse

Topics: IT security decision making human resource management social network government system

Methods: survey partial least squares path modeling cross sectional research mediation analysis archival research

Theories: protection motivation theory structuration theory

sPAN-pROP: Combatting Contextualized Social Media State-Linked Propaganda in the Middle East

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Aleroud, Ahmed; Melhem, Abdullah Bani; Alhussien, Nour; Albert, Craig

Abstract: Social Cyber-attacks such as propaganda, conspiracy theories, anger, and hate d ... Expand

Abstract: Social Cyber-attacks such as propaganda, conspiracy theories, anger, and hate discourse are very old phenomena that inflict harm to humans, organizations, national security, public officials, democratization efforts, careers, and policies. There have been significant efforts to identify anti-US speech on social media which includes propaganda. Such efforts largely ignore the attempts by other countries to manipulate social media in some regions including the Middle East. Research in this area is computational and solely focuses on fine tuning language models to detect general propaganda attacks. This paper addresses a new category of propaganda attacks that are tied to state-linked accounts that spread anti-US propaganda by taking advantages of specific geo-political crises in the Middle East. We investigated the role of general language models and training data to detect those forms of propaganda. Our study concludes that existing propaganda training data is unable to successfully detect targeted propaganda. We propose a contextualized span detection approach to identify these types of propaganda and show that our targeted training models work significantly better compared to the existing general propaganda detection approaches. Collapse

Topics: Twitter IT security threat social media armed conflict misinformation

Methods: language model experiment deep learning PyTorch literature study

Introduction to the Minitrack on Data Analytics, Data Mining, and Machine Learning for Social Media

2023 | HICSS | Citations: 0

Authors: Babb, J.; Mentzer, K.; Yates, D.

Abstract: Thank you for your interest in the Data Analytics, Data Mining, and Machine Le ... Expand

Abstract: Thank you for your interest in the Data Analytics, Data Mining, and Machine Learning for Social Media Minitrack. This year's paper contributions vary in scope and focus and thus provide a rich spectral view of developing insights and understanding from social media. According to Monique Thomas of Later, social media is experiencing a significant evolution: "We've said goodbye to simple status updates (we miss you!) and hello to social selling and growing digital communities." However, our digital communities continue to struggle with the challenge of being free and open, allowing anyone to express their thoughts and ideas, while at the same time working to combat misinformation and deep fakes. We are grateful to social media scholars who continue on various paths of sensemaking to better understand social media's impact on our society. This year's papers provide many new insights into this vital area of research. Collapse

Topics: social media misinformation privacy online community Twitter

Methods: structured literature research cluster analysis sentiment analysis case study

Applying Automated Text Analysis to Detect Ideologically-Motivated Manipulations in Mass-Media News

2023 | International Conference on Information Systems | Citations: 0

Authors: Babik, Iryna; Eker, Emily; Babik, Dmytro

Abstract: ... Expand

Abstract: Collapse

Topics: misinformation Google+

Methods: literature sample factorial experiment qualitative content analysis

A Signal Detection Theory Approach for Predicting Immunity to Pandemic Vaccine Fake News

2023 | HICSS | Citations: 0

Authors: Barajas, J.; John, R.

Abstract: Managing a contagious disease pandemic, such as , requires that the public unde ... Expand

Abstract: Managing a contagious disease pandemic, such as , requires that the public understand and cooperate with behavioral guidelines to reduce viral transmission. This research uses Signal Detection Theory (SDT) to explore how U.S. adults distinguish between true and false information related to COVID-19 vaccines. A total of 372 U.S. adults categorized 17 true and 17 false COVID-19 vaccine headlines. Item Response Theory analyses suggest that the ability to identify true information about the pandemic is a construct that can be reliably measured with our novel methodology. Signal Detection Theory analyses indicate high accuracy (AUC = 0.861), with no bias favoring either true or false responses. Overall, U.S. adults correctly classified 7 of 10 true and 8 of 10 false headlines. Multiple regression analyses on individual performance metrics reveal substantially lower accuracy among conservatives and those with lower scores on a measure of Actively Open-minded Thinking. Implications and limitations of these findings within the pandemic news context are discussed. Collapse

Topics: misinformation fake news pandemic social media covid 19

Methods: machine learning survey multiple linear regression survey design regression analysis method

Theories: signal detection theory

User Privacy, Surveillance and Public Health during COVID-19 – An Examination of Twitterverse

2023 | Information Systems Frontiers | Citations: 0

Authors: Bhatt, Paras; Vemprala, Naga; Valecha, Rohit; Hariharan, Govind; Rao, H. Raghav

Abstract: Online users frequently rely on social networking platforms to transmit public c ... Expand

Abstract: Online users frequently rely on social networking platforms to transmit public concerns and raise awareness about societal issues. With many government organizations actively employing social media data in recent times, the need for processing public concerns on social media has become a critical topic of interest across academic scholars and practitioners. However, the growing volume of social media data makes it difficult to process all the issues under a single umbrella, causing to overlook the main topic of interest within communication technologies, such as privacy. For example, during the COVID-19 pandemic, arguments on privacy and health issues exploded on Twitter, with several threads centered on contact tracking, health data gathering, and its usage by government agencies. To address the challenges of rising data volumes and to understand the importance of privacy concerns, particularly among users seeking greater privacy protection during this pandemic, we conduct a focused empirical analysis of user tweets about privacy. In this two-part research, our first study reveals three macro privacy issues of discussion distilled from the Twitter corpus, subsequently subdivided into 12 user privacy categories. The second study builds on the findings of the first study, focusing on the primary difficulties highlighted in the macro privacy subjects—contact tracing and digital surveillance. Using a document clustering approach, we present implications for the focal privacy topics that policymakers, agencies, and governments should consider for offering better privacy protections and help the community rebuild. Collapse

Topics: privacy Twitter social media pandemic information privacy concern

Methods: topic model qualitative content analysis cluster analysis hierarchical clustering Gensim

Can Fact-Checking Influence User Beliefs About Misinformation Claims: An Examination of Contingent Effects

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Bhattacherjee, Anol

Abstract: Prior research has suggested that corrective fact-checking has inconsistent eff ... Expand

Abstract: Prior research has suggested that corrective fact-checking has inconsistent effects on beliefs about online misinformation claims. This study attempts to explain this inconsistency using three contingent factorsclaim-source credibility, fact-checker credibility, and attitude strength-which respectively relate to three key parties in the fact-checking process: the source of a misleading claim, the fact-checker, and the user evaluating the fact-check. I hypothesize the interplay between these factors, which is tested using two online experiments on COVID-19-related misinformation with over 900 participants. Multilevel analysis of pretest-posttest, repeated measures data supports the hypothesized moderating effects and offers additional insights about how these effects vary between earlier versus later phases of misinformation cycles. The paper concludes with a discussion of contributions to research and practice. Collapse

Topics: misinformation pandemic BuzzFeed covid 19 user attitude

Methods: experiment regression analysis method longitudinal research statistical power analysis theoretical contribution

The Fault in Our Stars: Molecular Genetics and Information Technology Use

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Brown, Susan; Sias, Richard

Abstract: There is a growing interest in understanding the role of genetics in explaining ... Expand

Abstract: There is a growing interest in understanding the role of genetics in explaining heterogeneity in behaviors, including those related to information systems (IS). The majority of the recent genetics research focuses on searching the entire genome in genome-wide association studies (GWASs) to link DNA to human traits. The results of GWASs can be used on datasets to compute a measure of genetic propensity known as a polygenic score, or PGS. PGSs are widely viewed as the future of genetics research. We conducted an exploratory study, in the context of information technology (IT) use, to examine if the PGS approach can be used to better understand the role of genetics in IS research. Consistent with our hypotheses, genetic endowments associated with Educational Attainment and General Cognition positively predict technology use, and genetic endowments associated with Neuroticism, Depressive Symptoms, Myocardial Infarction, and Coronary Artery Disease negatively predict technology use more than half a century later (genetic endowments are established at conception and our sample consists of individuals aged 50 to 80). Many of the characteristics known to be associated with heterogeneity in IT use (e.g., trust, education) appear to be mediators linking PGSs to IT use. Nonetheless, a number of PGSs maintain meaningful direct effects.This appendix 26 provides additional background and details on molecular genetics, and some of the major issues surrounding the construction and use of GWASs and PGSs. For readers interested in learning more, we recommend Browne and Walden's (2020) Appendix A for additional details on molecular genetics and the structure of DNA, Duncan et al. (2019) for additional details on GWASs, Choi et al. (2020) for additional details on PGSs, and Freese (2018) and Harden and Koellinger (2020) for discussions on using PGSs in social science research. Collapse

Topics: information system use social media personality accounting video conference

Methods: survey mediation analysis descriptive statistic qualitative interview NeuroIS

Social Norms and Misinformation Sharing of Politicized Products

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Bui, Quang Neo; Moriuchi, Emi

Abstract: Misinformation has been on the rise, and in many cases, misinformation is inten ... Expand

Abstract: Misinformation has been on the rise, and in many cases, misinformation is intentionally shared for political reasons. This phenomenon first started with political news but now has spread in consumer products. To understand how misinformation sharing occurs differently between politized versus nonpoliticized products, we conducted an experiment and survey 800 respondents in an online crowdsourcing platform. The results show that for a politicized product, individual bias disposition and social norms indeed sway an individual's evaluation of information credibility, her trust and intention to share. However, this effect is not observed for non-politicized products. This call for more research to understand the role of social norms in stopping the spread of misinformation. Collapse

Topics: social norm social media misinformation crowdsourcing information exchange

Methods: parametric test structural equation modeling two-way ANOVA survey moderation analysis

Deploying Artificial Intelligence to Combat Covid-19 Misinformation on Social Media: Technological and Ethical Considerations

2023 | HICSS | Citations: 0

Authors: Cartwright, B.; Frank, R.; Weir, G.; Padda, K.; Strange, S.

Abstract: This paper reports on AI research into online misinformation pertaining to the ... Expand

Abstract: This paper reports on AI research into online misinformation pertaining to the COVID-19 pandemic within the Canadian context. This is part of our longerterm goal, i.e., development of a machine-learning tool to assist social media platforms, online service providers and government agencies in identifying and responding to misinformation on social media. We report on predictive accuracies accomplished by applying a combination of technologies, including a custom-designed web-crawler, The Dark Crawler, the Posit toolkit, and four different machine-learning models based on Naïve Bayes, Support Vector Machines, LibLinear and LibShortText. Overall, we found that Posit and LibShortText models showed higher levels of correlation to the pre-determined (manual and machine-driven) data classifications than the other machine-learning algorithms tested. We further argue that the harms associated with COVID-19 misinformatione.g., the social and economic damage, and the deaths and severe illnessesoutweigh the right to personal privacy and freedom of speech considerations. Collapse

Topics: misinformation Twitter Reddit social media pandemic

Methods: machine learning computational algorithm support vector machine decision tree classification random forest classification