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Pickled eggs: Generative AI as research assistant or co-author?
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2023 | Information Systems Journal | Citations: 0
Authors: Davison, Robert M.; Laumer, Sven; Tarafdar, Monideepa; Wong, Louie H. M.

Abstract: ChatGPT' indicates approximately 416 million hits, while Google Scholar suggest ... Expand

Abstract: ChatGPT' indicates approximately 416 million hits, while Google Scholar suggests 4710 articles, a number that is likely to rise fast. Generative AI is clearly here to stay, though there are already calls to curtail its use and some countries appear to be banning it. Interestingly, we already see the roll-out of generative AI detection software with tools like GPTZero. The plagiarism detection tool, iThenticate, is likely to follow up and embed generative AI detection as well. In order to reflect on this rapidly developing phenomenon, we conducted a sentiment and topic analysis of Twitter tweets about ChatGPT in academia. We analysed 12 400 tweets over a 3-month period from late 2022 to early 2023. 3680 tweets display a positive sentiment, 2612 display a negative one and 6109 display a neutral view. This pattern already exhibits a shift from the earlier reactions which were predominantly negative. Nevertheless, the topics discussed in these tweets are similar and can be subsumed within two major streams: research and publication. | WHY DOES IT MATTER TO ISJ READERS?Our focus in this editorial is on the practicalities of applying generative AI in the academic research community. The stakeholders of relevance here are authors, reviewers, editors and readers (scholars and practitioners) of ISJ, and also its publisher. All of these stakeholders have a commitment to and interest in the undertaking and publishing of academic research. Indeed, research and publication are the twin pillars on which a scholarly journal stands. Emerging articles comment on the strengths, weaknesses, opportunities and threats of generative AI in the context of research (see for instance Dwivedi et al., 2023, for an extensive account). In academia, there is an ongoing debate on the various implications that the technology may have. | WHY IS GENERATIVE AI RELEVANT TO RESEARCH?The title of this editorial, viz.: "pickled eggs", should have given some pause for thought. As it happened the collaborators of one of the co-authors of this editorial used a generative AI assistant (Microsoft Office 365's transcription function) to convert an audio file (of an interview with a research subject) to text. In that interview, reference was made to "pico-x", the name of a software. The generative AI assistant duly rendered this as "pickled eggs", presumably the closest term in its vocabulary. Reading through the transcript, numerous errors appeared: personal, product or place names were routinely misspelled, but so too were more mundane expressions. Similar errors occurred in Chinese where an interviewee used the English letters EDI (Electronic Data Interchange) in the middle of what was otherwise a Chinese sentence. The generative AI assistant, which was set up to transcribe Chinese audio to Chinese text, correctly transcribed all the Chinese words into characters, but made an error with EDI, which it also converted Collapse

Semantic filters: affect theory

Topics: Twitter knowledge sharing electronic health digital ecosystem participatory design

Methods: experiment survey design methodology action research chatGPT

Theories: affect theory
Satisfaction or gratitude? Exploring the disparate effects of physicians' knowledge sharing on patients' service evaluation in online medical consultations
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2023 | Information Systems Journal | Citations: 0
Authors: Tan, Hongying; Zhang, Xiaofei; Yang, Yefei

Abstract: The influence of physicians' knowledge sharing on patient satisfaction in online ... Expand

Abstract: The influence of physicians' knowledge sharing on patient satisfaction in online medical consultations (OMCs) has received extensive attention in recent years. However, patient gratitude in OMCs, another crucial outcome for physicians' knowledge sharing, has largely been overlooked. To address this gap, this study attempts to distinguish patient satisfaction from gratitude in OMCs and elucidate the relationship between the sharing process and outcomes. Drawing on the affect theory of social exchange, this study proposes a model that investigates the relative effects of physicians' informational and emotional support during the knowledge-sharing process on patient satisfaction and gratitude, as well as the contingent roles of physicians' professional seniority and patients' disease severity. The research model is tested by using data from a well-known online health platform in China. The results indicate that patient gratitude is associated with a more favourable service evaluation than satisfaction in OMCs. Physicians' informational support has a greater effect on patient satisfaction than emotional support, while emotional support has a greater effect on patient gratitude than informational support. Moreover, professional seniority and disease severity positively and negatively moderate the relationship between emotional support and patient gratitude, respectively. A survey-based experiment is also adopted to validate the research model with self-reported perceptual measures. This study contributes to the literature on patient gratitude, online healthcare service evaluation, knowledge sharing, and the affect theory of social exchange. Collapse

Semantic filters: affect theory

Topics: knowledge sharing online review healthcare data electronic health privacy

Methods: sentiment analysis Wald test survey experiment parametric test

Theories: affect theory
Why your Past Matters: Disentangling the Influence of “Static” and “Dynamic” Emotional Properties in Social Media Content on User Engagement

2021 | International Conference on Information Systems | Citations: 0
Authors: Alibakhshi, Reza; Srivastava, Shirish C.

Abstract: Grounding our work in the literature on emotion dynamics and affect theory of s ... Expand

Abstract: Grounding our work in the literature on emotion dynamics and affect theory of social exchange, we theorize an emotion-centric model for visual social media posts comprising both static and dynamic aspects of emotions. Specifically, we hypothesize and empirically evaluate the relative salience of 'peak visual emotion' displayed in a social media post versus the 'emotional variability' and 'emotional inertia' of posts from a profile owner in determining the longevity of user engagement. Through this study, we make three key contributions. First, we emphasize the importance of considering dynamic emotional features in addition to the static emotional attributes embedded in the context of visual social media posts. Second, we reiterate the economic rationale for examining the 'longevity of user engagement' with the visual social media posts as a measure of social media success. Finally, we complement prior studies offering novel emotion dynamics constructs and invaluable insights for social media practitioners. Collapse

Semantic filters: affect theory

Topics: social media Instagram online community marketing management Microsoft Azure

Methods: autoregressive integrated moving average longitudinal research image processing robustness check autoregressive model

Theories: affect theory information systems theory
Managers’ Responses to Online Reviews for Improving Firm Performance: A Text Analytics Approach
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2021 | Communications of the Association for Information Systems | Citations: 0
Authors: Deng, Tianjie; Lee, Young-Jin; Xie, Karen

Abstract: ... Expand

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Semantic filters: affect theory

Topics: online review organizational productivity financial performance social media missing data

Methods: natural language processing sentiment analysis product review cluster analysis link analysis

Theories: social exchange theory affect theory
Deep learning for affective computing: Text-based emotion recognition in decision support
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2018 | Decision Support Systems | Citations: 0
Authors: Kratzwald, Bernhard; Ilić, Suzana; Kraus, Mathias; Feuerriegel, Stefan; Prendinger, Helmut

Abstract: Emotions widely affect human decision-making. This fact is taken into account by ... Expand

Abstract: Emotions widely affect human decision-making. This fact is taken into account by affective computing with the goal of tailoring decision support to the emotional states of individuals. However, the accurate recognition of emotions within narrative documents presents a challenging undertaking due to the complexity and ambiguity of language. Performance improvements can be achieved through deep learning; yet, as demonstrated in this paper, the specific nature of this task requires the customization of recurrent neural networks with regard to bidirectional processing, dropout layers as a means of regularization, and weighted loss functions. In addition, we propose sent2affect, a tailored form of transfer learning for affective computing: here the network is pre-trained for a different task (i.e. sentiment analysis), while the output layer is subsequently tuned to the task of emotion recognition. The resulting performance is evaluated in a holistic setting across 6 benchmark datasets, where we find that both recurrent neural networks and transfer learning consistently outperform traditional machine learning. Altogether, the findings have considerable implications for the use of affective computing. Collapse

Semantic filters: affect theory

Topics: Twitter innovation management knowledge sharing decision support

Methods: deep learning experiment sentiment analysis machine learning word embedding

Theories: affect theory
SOUNDING OUT IS? MOODS AND AFFECTIVE ENTANGLEMENTS IN EXPERIENTIAL COMPUTING

2017 | European Conference On Information Systems | Citations: 0
Authors: Bødker, Mads; Jensen, Tina Blegind

Abstract: How do we experience living in a world in which soundscapes from digital technol ... Expand

Abstract: How do we experience living in a world in which soundscapes from digital technologies are increasingly pervading our everyday lives? In this paper, we pay attention to moods, ambiances, and other ephemeral aspects that give shape to how working with digital technology feels. Too often glossed over in search of more concrete narratives of ‘effect’ or ‘impact’ of digital technology, we argue that the socio-materiality of practice can be complemented by a notion of affective entanglement; i.e., the embodied materiality of feeling. Highlighting in particular how soundscapes and noise from ubiquitous computers performs and matters in the emergent composition of embodied being and subjectivity, we urge IS researchers to pay attention to everyday phenomena that involve digital technologies. Towards this aim, we present three autoethnographic vignettes that help unpack situations in which sounds shape or perform certain kinds of subjectivities and felt, embodied dispositions. Based on these everyday narratives, we analyse the different ways in which soundscapes from digital technology shape the body’s ability to act, feel, think, and experience. We conclude this research in progress paper by suggesting some opportunities for advancing a material, sensory, and ‘experiential turn’ in the IS discipline. Collapse

Semantic filters: affect theory

Topics: IS discipline mobile system embedded system smart wearable device knowledge representation

Methods: autoethnography experiment theory development ontological modelling

Theories: affect theory
Communicating Personal Health Information in Virtual Health Communities: An Integration of Privacy Calculus Model and Affective Commitment

2017 | Journal of the Association for Information Systems | Citations: 60
Authors: Kordzadeh, Nima; Warren, John

Abstract: Health consumers such as patients and caregivers often join virtual health commu ... Expand

Abstract: Health consumers such as patients and caregivers often join virtual health communities (VHCs) to seek and provide health-related information and emotional support. To do so, they converse with other individuals in platforms such as public discussion boards and blogs. During these online conversations, people may communicate their personal health information (PHI) to others. A potential driver for this form of revealing PHI is the immediate positive outcomes that it can provide for contributors and the community. PHI disclosure, however, can entail privacy risks and concerns for community members, which may ultimately hamper their participation in those communities. Moreover, one’s emotional attachment to a VHC (namely, affective commitment) may influence one’s PHI sharing behaviors in that community. Thus, to understand how various factors impact communicating PHI in public VHC discussions, we drew on the privacy calculus model and the notion of affective commitment, developed a theoretical model, and empirically tested the model. To do so, we administered a survey to individuals from three different populations including students, faculty, and staff at a large university and visitors to clinics. We performed a set of hierarchical moderated multiple regressions on the dataset. The results revealed that privacy concerns along with expected personal and community-related outcomes of communicating PHI affected willingness to communicate PHI in public VHC discussions. The results, however, refuted the hypothesized direct and moderating effects of affective commitment on willingness to share PHI in these virtual platforms. The findings of this study provide contributions to research and practice. Keywords: Online Social Networks, Virtual Health Communities, Personal Health Information, Privacy Calculus, Affective Commitment, Self-disclosure, Health Communication. Collapse

Semantic filters: affect theory

Topics: information privacy concern online community privacy social network data breach

Methods: survey regression analysis method data transformation principal component analysis ANOVA

Theories: privacy calculus theory affect theory social capital theory
AFFECT THEORY AND AUTOETHNOGRAPHY IN ORDINARY INFORMATION SYSTEMS

2016 | European Conference On Information Systems | Citations: 0
Authors: Bødker, Mads; Chamberlain, Alan

Abstract: This paper uses philosophical theories of affect as a lens for exploring autoeth ... Expand

Abstract: This paper uses philosophical theories of affect as a lens for exploring autoethnographic renderings of everyday experience with information technology. Affect theories, in the paper, denote a broad trend in post-humanistic philosophy that explores sensation and feeling as emergent and relational precognitive forces that impinge on a body and its capacity to act. A necessarily truncated account of affect theory, and three autoethnographic vignettes are presented to complement the philosophical exposition and to provide reflections on possible empirical tactics for affective research in IS. Inspired by the challenges to IS reflected in Yoo’s notion of Experiential Computing, the paper contributes with examples of how everyday attentiveness to the senses can unveil new forms of embodiment related to ‘living with technology’. It suggests that feelings (both sensory visceral as well as more generalized moods) emerge out of intimate embodied entanglement with ubiquitous computing technologies infrastructures. Collapse

Semantic filters: affect theory

Topics: ubiquitous computing knowledge representation decision making usability human computer interaction

Methods: autoethnography ontological modelling ethnography theory development netnography

Theories: affect theory sociomaterialism theory
Affective Primacy in Intraorganizational Task Networks
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2015 | Organization Science | Citations: 0
Authors: Casciaro, Tiziana; Lobo, Miguel Sousa

Abstract: To better understand the role of affect in organizational task-related networks, ... Expand

Abstract: To better understand the role of affect in organizational task-related networks, we developed a theory of affective primacy that identifies cognitive and motivational mechanisms through which the affective value of a social relationship (a feeling of positive affect from interactions with a colleague) operates as an antecedent of perceived instrumental value (a subjective evaluation of a relationship’s contribution to accomplishing assigned tasks). We tested this theory with full-network data collected over three years from employees in a small functional-form organization, which we analyzed with a methodology drawing from the social relations model of interpersonal perception and Bayesian models for social network analysis. We found that, over time, the affective value of social relationships influences both perceptions of instrumental value and the formation of task-related ties through multiple paths not accounted for by either perceived instrumental value or formal-structural requirements. We also show that the emergence of task-related networks rests primarily on high-activation positive emotions, such as excitement (a subjective state of feeling energized) rather than positive emotions with lower levels of activation, such as pleasantness (a subjective state of feeling gratified). We discuss implications of these findings for organizational theory and managerial practice. Collapse

Semantic filters: affect theory

Topics: task interdependence social identity organizational context cross cultural research organization structure

Methods: survey qualitative interview longitudinal research descriptive statistic theory development

Theories: general systems theory affect theory organizational theory
Sentiment Analysis Meets Semantic Analysis: Constructing Insight Knowledge Bases

2015 | International Conference on Information Systems | Citations: 0
Authors: Qi, Zirun; Storey, Veda; Jabr, Wael

Abstract: Numerous Web 2.0 applications collect user opinions, and other user-generated co ... Expand

Abstract: Numerous Web 2.0 applications collect user opinions, and other user-generated content in the form of product reviews, discussion boards, and blogs, which are often captured as unstructured data. Text mining techniques are important for analyzing users’ opinions (sentiment analysis) and identifying topics of interest (semantic analysis). However, little work has been carried out that combines semantics with user’s sentiments. This research proposes a Sentiment-Semantic Framework that incorporates results from both semantic and sentiment analysis to construct a knowledge base of insights gained from integrating the information extracted from each type of analysis. To evaluate the framework, a prototype is developed and applied to two different domains (e-commerce and politics) and the resulting insight knowledge bases constructed. Collapse

Semantic filters: affect theory

Topics: knowledge base user-generated content knowledge representation online review cloud storage

Methods: design artifact sentiment analysis part of speech tagging ontological modelling product review

Theories: affect theory

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Found 11 articles

Pickled eggs: Generative AI as research assistant or co-author?

Satisfaction or gratitude? Exploring the disparate effects of physicians' knowledge sharing on patients' service evaluation in online medical consultations

Why your Past Matters: Disentangling the Influence of “Static” and “Dynamic” Emotional Properties in Social Media Content on User Engagement

Managers’ Responses to Online Reviews for Improving Firm Performance: A Text Analytics Approach

Deep learning for affective computing: Text-based emotion recognition in decision support

SOUNDING OUT IS? MOODS AND AFFECTIVE ENTANGLEMENTS IN EXPERIENTIAL COMPUTING

Communicating Personal Health Information in Virtual Health Communities: An Integration of Privacy Calculus Model and Affective Commitment

AFFECT THEORY AND AUTOETHNOGRAPHY IN ORDINARY INFORMATION SYSTEMS

Affective Primacy in Intraorganizational Task Networks

Sentiment Analysis Meets Semantic Analysis: Constructing Insight Knowledge Bases