Augmenting Social Bot Detection with Crowd-Generated Labels

2023 | Information Systems Research | Citations: 0

Authors: Benjamin, Victor; Raghu, T. S.

Abstract: Social media platforms are facing increasing numbers of cyber-adversaries seekin ... Expand

Abstract: Social media platforms are facing increasing numbers of cyber-adversaries seeking to manipulate online discourse by using social bots (i.e., social media software robots) to help automate and scale their attacks. Likewise, some social media users can identify social bot activity at varying degrees of confidence. In this research, human reactions to social bot messages are used to augment existing social bot detection capabilities. Speech act theory is used to inspire a framework for assessing the credibility of instances where users identify potential bot activity, as not all user responses are of equal credibility for assisting with the bot detection task. The framework is then operationalized through deep learning methodologies to develop a computational system for identifying social bots. Real-world performance and practicality of the developed framework is demonstrated on a live, crowd-sourced data set collected from a real-world social media platform. Results show that consideration of crowd reactions to suspected bots can significantly improve bot detection performance. Furthermore, consideration of speech acts to evaluate crowd reactions can even further augment the system’s performance, although speech acts themselves are not necessary to observe performance boost through crowd intelligence. This study serves as a grounding point for future work that can explore an augmented model for detecting other forms of algorithmically generated content within social media platforms.History: Olivia Sheng, Senior Editor; Jesse Bockstedt, Associate Editor.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1136. Collapse

Topics: Reddit social media crowdsourcing IT productivity social media analytics

Methods: experiment BERT machine learning support vector machine random forest classification

Theories: speech act theory

Social Media Data in an Augmented Reality System for Situation Awareness Support in Emergency Control Rooms

2023 | Information Systems Frontiers | Citations: 0

Authors: Fromm, Jennifer; Eyilmez, Kaan; Baßfeld, Melina; Majchrzak, Tim A.; Stieglitz, Stefan

Abstract: During crisis situations, emergency operators require fast information access to ... Expand

Abstract: During crisis situations, emergency operators require fast information access to achieve situation awareness and make the best possible decisions. Augmented reality could be used to visualize the wealth of user-generated content available on social media and enable context-adaptive functions for emergency operators. Although emergency operators agree that social media analytics will be important for their future work, it poses a challenge to filter and visualize large amounts of social media data. We conducted a goal-directed task analysis to identify the situation awareness requirements of emergency operators. By collecting tweets during two storms in Germany we evaluated the usefulness of Twitter data for achieving situation awareness and conducted interviews with emergency operators to derive filter strategies for social media data. We synthesized the results by discussing how the unique interface of augmented reality can be used to integrate social media data into emergency control rooms for situation awareness support. Collapse

Topics: Twitter situation awareness augmented reality smart device social media

Methods: qualitative interview computational algorithm design principle machine learning qualitative content analysis

Social Media Analysis of Modifiable Lifestyle Factors in Multiple Sclerosis

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Gorugantu, Laxmi Manasa; El-Gayar, Omar; Nawar, Nevine

Abstract: Around 1 million people in the USA and 2.8 million people around the globe are ... Expand

Abstract: Around 1 million people in the USA and 2.8 million people around the globe are living with Multiple Sclerosis (MS), which currently has no cure. Incomplete recovery, long-term disability, worsening of symptoms leads to disruption in the Quality of Life among MS patients. However, modifiable lifestyle factors (MLFs) have demonstrated the potential to improve health and wellbeing in MS patients. Therefore, by leveraging social media analytics, this study aims to understand the public perspective on MLFs as reflected in the online generated information. The study identified topics pertaining to MLFs and evaluated the relative prevalence of these topics in social media discourse. The results and analysis showed th at Diet and Temperature are the two main factors for MS patients to constantly maintain and monitor. Further, this study can help the medical community in recommending the best lifestyle measure s that is necessary for an MS patient. Collapse

Topics: social media Twitter social media analytics Reddit social network

Methods: literature study survey

FINFLUENCERS: OPINION MAKERS OR OPINION FOLLOWERS?

2023 | European Conference On Information Systems | Citations: 0

Authors: Haase, Frederic; Rath, Oliver; Kurka, Marco; Schoder, Detlef

Abstract: This paper explores the concept of Finfluencers: financial social network actor ... Expand

Abstract: This paper explores the concept of Finfluencers: financial social network actors with high potential social influence. Our research aims to clarify whether Finfluencers drive or are influenced by the broader social network sentiment, thereby establishing their role as either opinion makers or opinion followers. Using a dataset of 71 million tweets focusing on stocks and cryptocurrencies, we grouped actors by their social networking potential (SNP). Next, we derived sentiment time series using state-ofthe-art sentiment models and applied the technique of Granger causality. Our findings suggest that the sentiment of Finfluencer actors on Twitter has short-term predictive power for the sentiment of the larger group of actors. We found stronger support for cryptocurrencies in comparison to stocks. From the perspective of financial market regulation, this study emphasizes the relevance of understanding sentiment on social networks and high social influence actors to anticipate scams and fraud. Collapse

Topics: Twitter social network social influence cryptocurrency social media

Methods: longitudinal research time series analysis Granger causality descriptive statistic sentiment analysis

Detection of Stock Manipulation Influencer Content using Supervised Learning

2023 | International Conference on Information Systems | Citations: 0

Authors: Haase, Frederic; Rath, Oliver; Lauten, Julia; Schoder, Detlef

Abstract: In recent years, social media influencers have emerged as key players in stock ... Expand

Abstract: In recent years, social media influencers have emerged as key players in stock manipulation schemes. Despite their growing impact, methods to detect such activities remain scarcely explored. In this study, we examine the social media content of stock manipulation influencers (SMIs) implicated in a $100 million fraud case by the U.S. Securities and Exchange Commission (SEC) in 2022. Leveraging natural language processing (NLP) techniques, we first investigate the linguistic characteristics present in the social media content published by SMIs. Next, we develop and evaluate supervised learning models to detect manipulative content. Our results have significant implications for investors, regulators, and the broader financial community. They reveal the unique linguistic characteristics of SMI content and demonstrate the potential of machinelearning and deep-learning-based techniques in advancing fraud detection systems. Collapse

Topics: Twitter social media fraud detection database system social media analytics

Methods: machine learning RoBERTa DistilBERT computational algorithm natural language processing

Do Early Words from New Ventures Predict Fundraising? A Comparative View of Social Media Narratives

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Havakhor, Taha; Golmohammadi, Alireza; Sabherwal, Rajiv; Gauri, Dinesh

Abstract: Online equity markets have significantly changed the dynamics of connecting ang ... Expand

Abstract: Online equity markets have significantly changed the dynamics of connecting angels and individual equity investors to new ventures that seek early-stage capital. However, for those early-stage investors, information pointing to the success of business-to-business (B2B) new ventures (B2BNVs) is scattered and disconnected. This paper focuses on social media narratives (SMNs) as a source of insight for such investors and proposes that predicting a B2BNV's likelihood of success requires a comparative view, i.e., a comparison of its SMNs with those of its competitors and customers. We expect that higher (lower) lingual similarity between the SMNs of an early-stage B2BNV and those of its prospective customers (competitors) predict its success. Using a longitudinal panel of 574 B2BNVs resulting in more than 2,700 venture-round observations, we find that a comparative view of a venture's SMNs can give early-stage investors reliable predictions about the B2BNV's ability to manage its market presence and its success in later stages. Our models show that a comparative view of SMNs increases the accuracy of predicting a B2BNV's later-stage fundraising success by an average of 15%. Furthermore, predictive models can reliably point to a successful market presence in later stages, including the landing of customers, the winning of awards and competitions, the receiving of endorsements, the generating of revenue, and the successful patenting of products. Our study contributes to existing literature that focuses on the business impacts of social media by demonstrating the usefulness of comparative linguistics in social media analytics, i.e., comparing the firm's social media communications to those of its competitors and business customers in the prediction of the entrepreneurial firm's success. Collapse

Topics: Twitter social media social media analytics social capital website

Methods: machine learning chi squared test latent dirichlet allocation robustness check theoretical contribution

Theories: lemon market theory

Signals of Transition in Crisis Management: Insights from a Study of Social Media Use in Public Service Organizations

2023 | HICSS | Citations: 0

Authors: Herrera, L.; Gjøsæter, T.; Majchrzak, T.; Thapa, D.

Abstract: In crisis informatics, little attention is placed on how transitions occur betw ... Expand

Abstract: In crisis informatics, little attention is placed on how transitions occur between periods of crisis and non-crisis. The analysis of transition behaviors in organizations could respond to both the cyclicality of risk and crisis management, and the need for continuity of services provided to the community. In studying transitions, we focus on social media use as a support system. Thus, with the objective to gain an insight into how sociotechnical systems navigate through periods of crisis and non-crisis, we leverage individual experiences that rely on social media as a source of information in public service organizations and developers of social media analytics support tools. The main contribution of this study is the explanation and conceptualization on how transitions happen by framing social media as a support system of information for crisis management. In addition, we highlight the return to a new steady-state, an overlooked area of organizational transitions and continuity. Collapse

Topics: social media emergency management social media analytics situational awareness information technology capability

Methods: qualitative interview theory development qualitative content analysis

Theories: punctuated equilibrium theory organizational behavior theory sociotechnical systems theory

Attributes of Continuity in Support Information Systems: A Study of Social Media Listening Experiences

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Herrera, Lucia Castro; Shahbazi, Maryam; Majchrzak, Tim A.; Gjøsæter, Terje; Bunker, Deborah

Abstract: The increasing recurrence of crises threatens the continuity of services provid ... Expand

Abstract: The increasing recurrence of crises threatens the continuity of services provided by public service organizations (PSOs) to their communities, especially those in need. Beyond contingency plans, PSOs must rely on robust support information systems able to withstand transitions between day-to-day activities and crisis response with as minimal interruptions as possible. Through the analysis of experiences of use of social media analytics as a support system in PSOs, this study proposes a set of attributes that take place while transitioning between non-crisis and crisis states. The sociotechnical nature of transitions calls for a zoomed-out analysis based on shared patterns that could lead to generalization in the future. The results of our study contribute towards understanding how continuity and equilibrium are exercised in volatile and dynamic environments. In addition, our results could help organizations self-assess their social media analytics teams or other support systems within the proposed parameters. Collapse

Topics: social media social media analytics emergency management pandemic problem solving

Methods: qualitative interview case study card sorting qualitative content analysis literature study

How Virtuous are Virtual Influencers? – A Qualitative Analysis of Virtual Actors’ Virtues on Instagram

2023 | HICSS | Citations: 0

Authors: Hofeditz, Lennart; Erle, Lukas; Timm, Lara; Mirbabaie, Milad

Abstract: Recently, virtual influencers (VIs) have become a more frequent alternative to h ... Expand

Abstract: Recently, virtual influencers (VIs) have become a more frequent alternative to human influencers (HIs). VIs can be described as non-human agents who behave in a human-like pattern. Big enterprises such as Prada, Porsche, Samsung, or Ikea have already collaborated with VIs in the past. Even though it should be clear to users that VIs cannot practice values and virtues in the real world, VIs seem to express certain virtues. This research paper focuses on identifying virtues conveyed by VIs and the effect of expressing virtues on follower engagement by conducting a qualitative content analysis of social media posts. Furthermore, we checked on VIs being abused by companies to convey a more favorable image. Our findings suggest that conveying certain virtues seems to have a positive effect on the engagement. In addition, some VIs were used by companies for virtue signaling without being noticed by their followers. Collapse

Topics: social media marketing management Instagram advertising management database system

Methods: qualitative content analysis survival analysis computational algorithm

Facilitators and Barriers of Artificial Intelligence Adoption in Business – Insights from Opinions Using Big Data Analytics

2023 | Information Systems Frontiers | Citations: 0

Authors: Kar, Arpan Kumar; Kushwaha, Amit Kumar

Abstract: Data-driven predictions have become an inseparable part of business decisions. A ... Expand

Abstract: Data-driven predictions have become an inseparable part of business decisions. Artificial Intelligence (AI) has started helping the product and support teams perform more accurate experiments in various business settings. This study proposes a framework for businesses based on inductive learnings related to success and barriers shared on social media platforms. Our goal is to analyse the signals emerging from these conversational opinions from the early adoption of AI, with a focus towards facilitators and barriers faced by teams. Factors like efficiency, innovation, business research, product novelty, manual intervention, adaptability, emotion, support, personal growth, experiential learning, fear of failure and fear of upgradation have been identified based on an exploratory study and then a confirmatory study. We present the learnings through a roadmap for practitioners. This study contributes to the IS literature by delineating AI as a determinant of success and introduces a lot of organizational factors into the model. Collapse

Topics: artificial intelligence Twitter innovation management big data social media

Methods: topic model literature study synthesis regression analysis method data transformation

Theories: organizational theory organizational behavior theory management theory technology acceptance model organizational learning theory