Understanding Emojis for Financial Sentiment Analysis

2023 | International Conference on Information Systems | Citations: 0

Authors: Chen, Siyi; Xing, Frank

Abstract: ... Expand

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Topics: application programming interface social media website cryptocurrency Python

Methods: sentiment analysis machine learning BERT deep learning experiment

The Opportunity in Difficulty: A Dynamic Privacy Budget Allocation Mechanism for Privacy-Preserving Multi-dimensional Data Collection

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Chen, Xue; Wang, Cheng; Yang, Qing; Hu, Teng; Jiang, Changjun

Abstract: Data collection under local differential privacy (LDP) has been gradually on the ... Expand

Abstract: Data collection under local differential privacy (LDP) has been gradually on the stage. Compared with the implementation of LDP on the single attribute data collection, that on multi-dimensional data faces great challenges as follows: (1) Communication cost. Multivariate data collection needs to retain the correlations between attributes, which means that more complex privatization mechanisms will result in more communication costs. (2) Noise scale. More attributes have to share the privacy budget limited by data utility and privacy-preserving level, which means that less privacy budget can be allocated to each of them, resulting in more noise added to the data. In this work, we innovatively reverse the complex multi-dimensional attributes, i.e., the major negative factor that leads to the above difficulties, to act as a beneficial factor to improve the efficiency of privacy budget allocation, so as to realize a multi-dimensional data collection under LDP with high comprehensive performance. Specifically, we first present a Multivariate k-ary Randomized Response (kRR) mechanism, called Multi-kRR. It applies the RR directly to each attribute to reduce the communication cost. To deal with the impact of a large amount of noise, we propose a Markov-based dynamic privacy budget allocation mechanism Markov-kRR, which determines the present privacy budget (flipping probability) of an attribute related to the state of the previous attributes. Then, we fix the threshold of flipping times in Markov-kRR and propose an improved mechanism called MarkFixed-kRR, which can obtain more optimized utility by choosing the suitable threshold. Finally, extensive experiments demonstrate the efficiency and effectiveness of our proposed methods. Collapse

Topics: privacy marketing management differential privacy data quality local differential privacy

Methods: computational algorithm experiment lasso regression archival research survey

Trust in Online Ride-Sharing Transactions: Impacts of Heterogeneous Order Features

2023 | Journal of Management Information Systems | Citations: 0

Authors: Cheng, Xusen; Fu, Shixuan; Sun, Jianshan; Zuo, Meiyun; Meng, Xiangsong

Abstract: With the development of the sharing economy, online ride-sharing has become a pr ... Expand

Abstract: With the development of the sharing economy, online ride-sharing has become a primary form of commuting. Using secondary transaction data, this study investigates the associations between the heterogeneous features and mutual trust in sharing economy-driven online ride-sharing transactions. Based on an examination of 12,404 ride-sharing orders in Beijing, we propose a set of trust distribution maps using order location data to reveal heterogeneous spatial patterns of the relationship between online ride-sharing transactions and mutual trust. The results show that the historical order completion rate and order distance are positively associated with mutual trust in ride-sharing transactions, whereas order time and departure density negatively and significantly influence mutual trust. Furthermore, we use machine learning algorithms to predict trust. The implications for theory and practice and future research directions are discussed. Collapse

Topics: ride sharing platform sharing platform logistics management geographic information system online review

Methods: machine learning computational algorithm regression analysis method experiment exploratory data analysis

Theories: signaling theory

Evaluating a Conversational Agent for Open Government Data Quality Assessment

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Chokki, Abiola Paterne; Clarinval, Antoine; Simonofski, Anthony; Vanderose, Benoît

Abstract: Governments have been publishing Open Government Data (OGD) on online portals t ... Expand

Abstract: Governments have been publishing Open Government Data (OGD) on online portals to encourage the development of value-added services. The success of these services depends heavily on the quality of OGD and its metadata. Several methods have been proposed to evaluate this quality, but some rely on manual assessments, which can be time-consuming and expensive to perform. Furthermore, these methods focus on the portal rather than the data, ignore user preferences, or do not distinguish between metadata and data quality. This makes it difficult for users to identify data quality issues. This paper proposes a list of OGD quality dimensions for assessing data and metadata quality. The dimensions were identified through a literature review and integrated into a novel conversational agent that incorporates user preferences into the quality assessment. A usability evaluation with 14 users reveals its ease of use and usefulness for obtaining overall and detailed (meta)data quality. Collapse

Topics: conversational agent ease of use data quality usability open data

Methods: design artifact survey literature study usability testing chatbot

Theories: technology acceptance model

Navigating within the Digitalization Journey: Results and Implications of the First Maturity Assessment of German Public Health Agencies

2023 | International Conference on Business Informatics | Citations: 0

Authors: Kauffmann, Anna Lina; Neubauer, Maria; Reinsch, Felix; Reuther, Melina; Schick, Doreen; Stark, Jeannette; Bley, Katja; Heidmann, Nick; Eymann, Torsten

Abstract: The Covid 19 pandemic revealed the need for Public Health Agencies to mature di ... Expand

Abstract: The Covid 19 pandemic revealed the need for Public Health Agencies to mature digitally. To help those agencies with their digitalization endeavor, a public health agency maturity model (PHAMM) has been developed, evaluated, and employed by 366 institutions to determine their digital maturity and to prioritize actions within digitalization projects. This paper discusses the digital maturity of German public health institutions and derives first insights into components spanning the PHAMM dimensions. Public health agencies can use these components to leverage their digital maturity in future digitalization projects. Implications are discussed for how digitalization projects with an enhanced impact can be defined and for future maturity modeling research. Collapse

Topics: IS maturity user friendliness system efficiency usability situation awareness

Methods: data transformation principal component analysis survey maturity model design science

Theories: balance theory situation awareness theory

Customer Responses to (Im)Moral Behavior of Service Robots Online Experiments in a Retail Setting

2023 | HICSS | Citations: 0

Authors: Kegel, M.; Stock-Homburg, R.

Abstract: Service robots play an increasingly important role in the service sector. Drawi ... Expand

Abstract: Service robots play an increasingly important role in the service sector. Drawing on moral psychology research, moral foundations theory as well as the computers-as-social-actors (CASA) paradigm, this experimental study containing of four online experiments examines the extent to which the moral or immoral behavior of a service robot affects customer responses during a service interaction. This study contributes to design science by defining, conceptualizing and operationalizing morality of service robots and developing a corresponding vignette as basis to manipulate (im)moral robotic behavior in a retail setting. To investigate possible effects of the robot's appearance, we tested our hypotheses with two different robots, i.e., a humanoid robot and an android robot. Results from the online experiment indicate that the (im)moral behavior of service robots at the customer interface has a significant effect on customers' trust and customers' ethical concerns towards the robot. Collapse

Topics: robotic data quality marketing management

Methods: experiment design science data transformation Student's t-test factor analysis

Theories: uncanny valley theory

Social informedness and investor sentiment in the GameStop short squeeze

2023 | Electronic Markets | Citations: 2

Authors: Kim, Kwansoo; Lee, Sang-Yong Tom; Kauffman, Robert J.

Abstract: We examine investor behavior on social media platforms related to the GameStop ( ... Expand

Abstract: We examine investor behavior on social media platforms related to the GameStop (GME) short squeeze in early 2021. Individual investors stimulated the stock market via Reddit social posts in the presence of institutional investors who bet against GME’s success as short sellers. We analyzed r/WallStreetBets subreddit posts related to GME’s trading patterns. We performed text-based sentiment analysis and compared the social informedness of posting users for GME trading on two social media platforms. The short squeeze occurred due to coordinated trading by individual investors, who discussed trading strategies on the platforms and drove collective social informedness-based trading behavior. Our findings suggest that the valence and number of submissions influenced GME’s intraday transaction volumes and precursors for irrational trading behavior patterns to have emerged. We provide a theoretical interpretation of what occurred and call for tighter monitoring of social news platforms. We also encourage effort to create an in-depth understanding of the observed patterns and the linkages between them and the larger equity markets. Collapse

Topics: Reddit social media Twitter analytical information system Python

Methods: Student's t-test sentiment analysis longitudinal research econometric modeling case study

Theories: cognitive dissonance theory

Trust antecedents in online reviews across national cultures

2023 | Decision Support Systems | Citations: 0

Authors: Kim, Youngeui; Srite, Mark; Zhao, Huimin

Abstract: When reading an online review, consumers rely on implied trust-building factors ... Expand

Abstract: When reading an online review, consumers rely on implied trust-building factors within it. Trust antecedents have been extensively researched and categorized into argument quality and source credibility. However, there is still a need to investigate how their help for consumers differs across national cultures. Furthermore, while a profile photo has been found to enhance the helpfulness of a review by improving source credibility, little is known about how consumers perceive user appearance in a review picture and no research has compared these two types of visual information. To bridge these gaps, we examine how trust antecedents and visual information help consumers’ decision making differently across national cultures, using reviews collected from Amazon in the US and Germany, respectively. Our results show that information quality is more helpful for consumers in an individualistic and low uncertainty avoidance culture, whereas source credibility is more valued in the opposite culture. Interestingly, the effects of the two types of visual information, user appearance in a profile photo versus in a review picture, also differ across cultures. This research contributes to the online review literature by introducing visual information and national culture with new perspectives of trust. Our findings suggest that multinational e-commerce businesses adopt culture-specific strategies in review systems to better help consumers make informed purchase decisions. Collapse

Topics: national culture online review Vine data quality information retrieval

Methods: robustness check topic model term frequency–inverse document frequency propensity score method natural language processing

Enhancing Perceived Fairness of AI-Based Personnel Selection Procedures: The Role of AI Certification

2023 | International Conference on Information Systems | Citations: 0

Authors: Kleiner, Romina; Hartwich, Nicole; Antons, David

Abstract: Organizations increasingly integrate artificial intelligence (AI) into their se ... Expand

Abstract: Organizations increasingly integrate artificial intelligence (AI) into their selection procedures, for example, to analyze selection interviews. However, prior research indicates that applicants react negatively to an AI as decision agent in selection interviews. Only few studies have addressed possible mechanisms to mitigate negative effects of AI usage on applicant reactions, calling for increased research attention. The present experimental study (N=180) is among the first to test whether AI certification has the potential to positively influence people's fairness perceptions of AI usage. Consistent with previous research, our results show that people are less attracted to an organization that conducts AI-based (compared to human-based) selection interviews, partially due to lower procedural fairness perceptions. With regards to AI certification, we highlight the crucial role of the certification label's perceived trustworthiness in shaping applicants' procedural fairness perceptions and organizational attraction. Future research should investigate factors that enhance the trustworthiness of an AI certification label. Collapse

Topics: artificial intelligence electronic commerce pandemic data quality anonymity

Methods: qualitative interview experiment mediation analysis statistical hypothesis test experimental design

Theories: signaling theory management theory procedural justice theory

Laboratory Forensics for Open Science Readiness: an Investigative Approach to Research Data Management

2023 | Information Systems Frontiers | Citations: 0

Authors: Lefebvre, Armel; Spruit, Marco

Abstract: Recently, the topic of research data management has appeared at the forefront of ... Expand

Abstract: Recently, the topic of research data management has appeared at the forefront of Open Science as a prerequisite for preserving and disseminating research data efficiently. At the same time, scientific laboratories still rely upon digital files that are processed by experimenters to analyze and communicate laboratory results. In this study, we first apply a forensic process to investigate the information quality of digital evidence underlying published results. Furthermore, we use semiotics to describe the quality of information recovered from storage systems with laboratory forensics techniques. Next, we formulate laboratory analytics capabilities based on the results of the forensics analysis. Laboratory forensics and analytics form the basis of research data management. Finally, we propose a conceptual overview of open science readiness, which combines laboratory forensics techniques and laboratory analytics capabilities to help overcome research data management challenges in the near future. Collapse

Topics: data management data quality digital forensics digital dashboard digital transformation

Methods: experiment digital trace data case study design artifact exploratory data analysis

Theories: semiotic theory theory of information information systems theory