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

To Brush or Not to Brush: Product Rankings, Consumer Search, and Fake Orders

2023 | Information Systems Research | Citations: 0

Authors: Jin, Chen; Yang, Luyi; Hosanagar, Kartik

Abstract: Brushing—online merchants placing fake orders of their own products—has been a w ... Expand

Abstract: Brushing—online merchants placing fake orders of their own products—has been a widespread phenomenon on major e-commerce platforms. One key reason why merchants brush is that it boosts their rankings in search results. Products with higher sales volume are more likely to rank higher. Additionally, rankings matter because consumers face search frictions and narrow their attention to only the few products that show up at the top. Thus, fake orders can affect consumer choice. We focus on this search-ranking aspect of brushing and build a stylized model to understand merchants’ strategic brushing behavior as well as how it affects consumers. We consider a high-type merchant (who sells a more popular product) and a low-type merchant (who sells a less popular product) competing on an e-commerce platform where product rankings evolve over time. We find that if brushing gets more costly for merchants (e.g., due to stricter platform policies), it may sometimes surprisingly harm consumers as it may only blunt brushing by the high-type merchant but intensify brushing by the low-type merchant. If search is less costly for consumers (e.g., due to improved search technologies), it may not always benefit consumers, either. Moreover, the design of the ranking algorithm is critical: placing more weight on sales-volume-related factors may trigger a nonmonotone change in consumer welfare; tracking recent sales only as opposed to cumulative sales does not always dial down brushing and, in fact, may sometimes cause the low-type merchant to brush more.History: Ravi Bapna, Senior Editor; De Liu, Associate Editor.Funding: C. Jin gratefully acknowledges the Singapore Ministry of Education Academic Research Fund [Tier 1, Grant R-253-000-144-133], The Wharton School Dean’s Postdoctoral Research Fund, and Mack Institute Research Fund. All authors gratefully acknowledge the 2019 Networks, Electronic Commerce and Telecommunications Institute (NET) Summer Research Grant.Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.1128. Collapse

Topics: IS economics consumer surplus electronic commerce fake review electronic market

Methods: computational algorithm literature sample

Theories: economic search theory

The Role of Media Synchronicity Fit and Sense of Community in Live Streaming Platforms

2023 | International Conference on Information Systems | Citations: 0

Authors: Liu, Yuqian; Deng, Chaoqun

Abstract: To understand viewers' sense of community in the live streaming environment, th ... Expand

Abstract: To understand viewers' sense of community in the live streaming environment, this research synthesizes media synchronicity theory and sense of community theory to develop a theoretical framework. We aim to examine the antecedents and consequences of the sense of community in live streaming platforms. We expect that viewers' actual communication purpose (e.g., conveyance or convergence) will influence viewers' sense of community in the live streaming context and further impact their activities in traditional third-party online communities. We first use experiments to validate the mechanism in our theoretical model and then collect observational data from Twitch, a popular live streaming platform, to test our hypotheses. Our results will provide theoretical contributions to the live streaming, online community, and communication literature. Our findings will provide practical implications for streamers in the live streaming platform. Collapse

Topics: live streaming platform Twitch online community social media user behavior

Methods: experiment descriptive statistic qualitativ observational study theoretical contribution theory development

Theories: media synchronicity theory

Why some products compete and others don't: A competitive attribution model from customer perspective

2023 | Decision Support Systems | Citations: 0

Authors: Qian, Yang; Jiang, Yuanchun; Shang, Jennifer; Chai, Yidong; Liu, Yezheng

Abstract: Competitive intelligence uses information collected about competitors to derive ... Expand

Abstract: Competitive intelligence uses information collected about competitors to derive better managerial insights. In this study, we focus on identifying the competitors and detecting the competitive dimensions concurrently. To achieve this goal, we propose an aspect-level competitive attribution model (a variation of the topic model) to leverage consumer-reviewed products and their review texts. To better analyze product relations and the un­ derlying competitive aspects, we consider consumer limited attention when modeling consumers' preferences and introduce a background aspect to filter out the trivial and maintain the valuable competition-related in­ formation in review texts. We validate this approach using a dataset of 785 products reviewed by 15,669 con­ sumers in the auto industry. Based on the empirical experiments, we show that our model can accurately infer high-quality competitive segments and decipher competition-related aspects corresponding to these segments. To highlight differences, we conduct comparisons and find our approach outperforms the benchmark models meaningfully in the literature when predicting consumers' online behaviors. Collapse

Topics: online review competitive intelligence marketing management competitive advantage user-generated content

Methods: topic model experiment Gibbs sampling natural language processing computational algorithm

Problem Specification in Crowdsourcing Contests: A Natural Experiment

2023 | International Conference on Information Systems | Citations: 0

Authors: Ye, Kai; Koh, Tat Koon

Abstract: Problem specification is a key aspect in crowdsourcing contests through which s ... Expand

Abstract: Problem specification is a key aspect in crowdsourcing contests through which seekers convey their requirements and taste for the desired submissions. Hence, it is important to understand how problem specification should be framed to achieve better crowdsourcing contest outcomes. In this empirical study, we investigate the effects of a relatively more structured problem specification on contest quantity, solver quantity, and idea quality. We leverage a natural experiment set up on a major crowdsourcing contest platform where the problem specification of logo design contests changed from openended to structured. Our results show that the specification change impacts both seekers and solvers. Specifically, the number of contests increases after the change but solver quantity and idea quality in the respective contests tend to be lower. We discuss the theoretical and practical contributions of this research. Collapse

Topics: crowdsourcing web page self efficacy task characteristic web crawling

Methods: theory development experimental group longitudinal research natural experiment event study

The dynamic effect of interactivity on customer engagement behavior through tie strength: Evidence from live streaming commerce platforms

2021 | International Journal of Information Management | Citations: 23

Authors: Kang, Kai; Lu, Jinxuan; Guo, Lingyun; Li, Wenlu

Abstract: Interactivity, which is a key characteristic of the live streaming commerce envi ... Expand

Abstract: Interactivity, which is a key characteristic of the live streaming commerce environment, fosters users’ active attitudes and behaviors in communications and transactions. However, the literature on live streaming com­ merce, is scarce, and few studies examine how interactivity influences customers’ non-transactional behaviors from a dynamic perspective. In this setting, based on the stimulus-organism-response (S-O-R) framework, we developed a research model using real-time data to investigate the dynamic effect of interactivity on customer engagement behavior through tie strength in live streaming commerce, which is a relatively new derivative of social commerce. This study developed a text mining method to quantify constructs using a large-scale sample of 3,500,445 online review texts. Our empirical study found that interactivity has a curvilinear relationship with customer engagement behavior. Besides, tie strength plays an intermediary role between interactivity and customer engagement behavior. It was further observed that both tenure of membership and popularity have an important moderating relationship between interactivity and tie strength. The study enriches the relationship marketing theory and live streaming commerce literature. Moreover, this study is one of the first studies to use real-time online data for live streaming commerce research. Collapse

Topics: personalization usability online review big data email spam

Methods: natural language processing word2vec conceptual modelling part of speech tagging survey

Theories: marketing theory

A WEB-CRAWLING BASED STUDY ON SERVITIZATION: ANALYSIS OF SERVICE OFFERINGS BY GERMAN MANUFACTURERS OF MACHINERY AND EQUIPMENT

2021 | European Conference On Information Systems | Citations: 0

Authors: Kreyenborg, Alexander; Austerjost, Maximilian; Groll, Mirco

Abstract: The machinery and equipment industry is, next to the automotive industry, the s ... Expand

Abstract: The machinery and equipment industry is, next to the automotive industry, the sector with the highest turnover in Germany. Here, servitization is a crucial contribution to remain competitive. Nevertheless, the diversity of this industry is not sufficiently taken into account in the scientific community. To overcome this gap, this study utilizes a web-crawling based approach to analyze service offerings of German manufacturers, linking key company figures to investigate potential correlations. This contribution differs from conventional studies using databases that hardly contain any detailed service information of smaller manufacturers. The proposed approach derives a clearer picture of the current service portfolio, considering all company sizes and its degree of servitization, enabling comparisons between micro-, small-, medium-and large-sized manufacturers. In context of digital servitization, the study allows further conclusions about the range of so-called basic services or advanced services and how these are related to key company figures. Collapse

Topics: web crawling database system website digital service business model

Methods: computational algorithm descriptive statistic

Understanding the Platform Economy

2020 | HICSS | Citations: 0

Authors: Hesse, Maik; Dann, David; Braesemann, Fabian

Abstract: Two-sided markets are gaining increasing importance. Examples include accommodat ... Expand

Abstract: Two-sided markets are gaining increasing importance. Examples include accommodation and car sharing, resale, shared mobility, crowd work, and many more. As these businesses rely on transactions among users, central aspects to virtually all platforms are the creation and maintenance of trust. While research has considered effects of trust-building on diverse platforms in isolation, the overall platform landscape has received much less attention. However, cross-platform comparison is important since platforms vary in their degree of social interaction, which, as we demonstrate in this paper, determines the adequacy and use of different trust mechanisms. Based on actual market data, we examine the mechanisms platforms employ and how frequent users rely on them. We contrast this view against survey data on users’ perceptions of the context-specific importance of these trust-building tools. Our findings provide robust evidence for our reasoning on the relation between platforms’ degree of social interaction and the associated expressive trust cues. Collapse

Topics: Airbnb crowdsourcing ride sharing platform frequency of use electronic commerce

Methods: survey regression analysis method personal interview qualitative coding self reported survey

Assessing the product review helpfulness: Affective-Cognitive evaluation and the moderating effect of feedback mechanism

2020 | Information & Management | Citations: 0

Authors: Li, Mengxiang; Huang, Pu

Abstract: Product review length has been demonstrated as one of the key factors that influ ... Expand

Abstract: Product review length has been demonstrated as one of the key factors that influence the product review helpfulness. However, we have little knowledge of a deeper understanding on how consumers process the product review length to assess product review helpfulness. Anchoring on the human’s affective-cognitive model of decision-making and the prominent coping approaches, this research revisits this key issue from consumers’ affect-oriented and cognition-oriented processing perspective. Our findings show that (1) consumers apply both the affect-oriented and cognition-oriented processing to assess the helpfulness of product review, (2) a significant inverted U-shape relationship between the review length and the review helpfulness, and interestingly, (3) such a relationship is further moderated by whether the product review author has provided a response to consumers’ comments. These findings not only provide further robust evidence to the consideration of both product review length and feedback, but also suggest a refinement of the underlying mechanism on how consumers process product review length to assess product review helpfulness. Collapse

Topics: online review website electronic commerce decision making web crawling

Methods: product review experiment experimental group laboratory experiment statistical hypothesis test

Improving high-tech enterprise innovation in big data environment: A combinative view of internal and external governance

2020 | International Journal of Information Management | Citations: 0

Authors: Lin, Runhui; Xie, Zaiyang; Hao, Yunhong; Wang, Jie

Abstract: The emergence of big data brings both opportunities and challenges to high-tech ... Expand

Abstract: The emergence of big data brings both opportunities and challenges to high-tech enterprises. How to keep competitive advantages and improve innovation performance is important for enterprises in big data environment. Except from organizational learning ability and the use of advanced technology, the corporate governance also plays an important role in the process of enterprise’s innovation practice. This article creatively combines with the insights of internal and external governance, and explores how the managerial power and network centrality affects enterprise’s innovation performance in big data environment. Considering about the differences among distinct regional big data environment (strong/weak), this paper also takes classification research on it. The research findings show that managerial power has a significant positive impact on innovation performance, managerial power could enhance enterprise’s centrality in network, and the enterprise which located in network central position has more advantages in obtaining resources and significantly improves firm’s innovation performance. Network centrality plays a mediating role on managerial power and innovation performance. Further research finds that the positive effects of managerial power and network centrality are more significantly in the strong big data environment. These findings enrich the research of high-tech enterprise innovation from a combinative governance view, and contribute to the literatures on enterprise innovation in big data environment. Collapse

Topics: innovation management big data corporate governance database system web crawling

Methods: statistical hypothesis test instrumental variables estimation qualitative interview computational algorithm social network analysis

Theories: theory of economic development