A Multi-Appeal Model of Persuasion for Online Petition Success: A Linguistic Cue-Based Approach

Yan, Chen; Deng, Shuyuan; Kwak, Dong-Heon; Elnoshokaty, Ahmed; Wu, Jiao

doi:10.17705/1jais.00530

Cited by 16 publications

(8 citation statements)

References 55 publications

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“…Furthermore, in another case study on textual conversations of CEOs and businesses, individuals process information from the peripheral route of the ELM would do so based on one of four appeals channels (social, ethical, political, and ideological) (Pignot, Nicolini, and Thompson 2020). However, much of the current research on human persuasion tend to rely on subject survey's asking the individual if the individual were persuaded (Yi et al 2019), at the aggregate (Chen et al 2019;Wang et al 2021a), or attempt to model receptiveness to phrasing (Pignot, Nicolini, and Thompson 2020). The literature lacks a definitive, easily identified indicator of detecting intention to action.…”

Section: Detecting Cases Of Persuasion On Redditmentioning

confidence: 99%

Turning Stocks into Memes: A Dataset for Understanding How Social Communities Can Drive Wall Street

Alvarez¹,

Bhatt²,

Xingmeng³

et al. 2022

Preprint

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Who actually expresses an intent to buy GameStop shares on Reddit? What convinces people to buy stocks? Are people convinced to support a coordinated plan to adversely impact Wall Street investors? Existing literature on understanding intent has mainly relied on surveys and self reporting; however there are limitations to these methodologies. Hence, in this paper, we develop an annotated dataset of communications centered on the GameStop phenomenon to analyze the subscriber intentions behaviors within the r/WallStreetBets community to buy (or not buy) stocks. Likewise, we curate a dataset to better understand how intent interacts with a user's general support towards the coordinated actions of the community for GameStop. Overall, our dataset can provide insight to social scientists on the persuasive power to buy into social movements online by adopting common language and narrative. WARNING: This paper contains offensive language that commonly appears on Reddit's r/WallStreetBets subreddit.

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Section: Detecting Cases Of Persuasion On Redditmentioning

confidence: 99%

Turning Stocks into Memes: A Dataset for Understanding How Social Communities Can Drive Wall Street

Alvarez¹,

Bhatt²,

Xingmeng³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The rationale is that increasing cognitive effort facilitates members to explore the central benefits and features of a stimulus (Kwak et al., 2019). According to the persuasion literature (e.g., Petty & Cacioppo, 1986), when a person carefully and thoughtfully considers the true merits of the information presented, he or she can spend cognitive effort to assess object‐relevant information, such as objective usability (Kwak et al., 2018; Chen et al., 2019). Through playing with ERPsim, a focused learner is likely to perceive the objective usability of ERPsim.…”

Section: Research Model and Hypothesesmentioning

confidence: 99%

Effect of team cohesion on flow: An empirical study of team‐based gamification for enterprise resource planning systems in online classes

Zhao

Srite

Kim

et al. 2021

Decision Sci J Innov Edu

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Pedagogy using gamification has recently received much attention as a way of enhancing student learning and retention. Additionally, academic institutions are making extensive use of online resources to expand teaching beyond the traditional classroom setting. Both academic institutions and companies utilize virtual teams to accomplish remote teamwork, particularly in a post-COVID environment. Despite the growing interest in incorporating gamification into teaching for business school courses, prior researchers have paid little attention to team-based gamification in the online learning environment. The purpose of this study is to examine if team members' perceived team cohesion influences their perceptions of flow. Also, we investigate the relationships among three flow dimensions: concentration, perceived control, and perceived enjoyment. We tested our research model using an enterprise resource planning simulation game involving 187 business students. The results of structural equation modeling with partial least squares analysis support all of our hypotheses.

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“…Theories guiding the research might also be from "pre-online times" as observed by [36] with social movement theories. As noted in [38], there is a need for future research to "develop new theories for capturing linguistic and other patterns in the rich, abundant content generated by ICT communication". They also note that a further study combining quantitative and qualitative analysis is needed of the factors influencing petition success and recommend focusing on videos and pictures related to the petitions.…”

Section: Lack Of Qualitative Toolsmentioning

confidence: 99%

“…Qualitative data and research are denoted by "rich descriptions", but quantification of qualitative data reduces this richness. For example, a petition might be unreasonable to begin with and this is something the algorithms cannot account for [38]. The unsupervised tools often focus on term frequencies and might miss less frequent terms meaning that the result is not representative of the whole content but a picture of what is popular [41,62].…”

Section: Tool Induced Lack Of Depthmentioning

confidence: 99%

See 1 more Smart Citation

Qualitative Big Data’s Challenges and Solutions: An Organizing Review

Suvivuo¹

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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Digitalization of everyday lives has tremendously increased the amount of digital (trace) data of people's behaviour available for researchers. However, traditional qualitative research methods struggle with the width and breadth of the data. This paper reviewed 61 recent studies that had utilized qualitative big data for the practical challenges they had encountered and how they were addressed. While quantitative and qualitative big data share many common issues, the review points at that lack of qualitative methods and dataset reduction required by algorithms in big data research decreases the richness of the qualitative data. Locating relevant data and reducing noise are further challenges. Currently, these challenges can be only partially addressed with a combination of human and computer pattern recognition and crowdsourcing. The review describes many "tricks of the trade" but abduction research and pragmatist philosophy seem promising starting places for a more pervasive framework.

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A Multi-Appeal Model of Persuasion for Online Petition Success: A Linguistic Cue-Based Approach

Cited by 16 publications

References 55 publications

Turning Stocks into Memes: A Dataset for Understanding How Social Communities Can Drive Wall Street

Turning Stocks into Memes: A Dataset for Understanding How Social Communities Can Drive Wall Street

Effect of team cohesion on flow: An empirical study of team‐based gamification for enterprise resource planning systems in online classes

Qualitative Big Data’s Challenges and Solutions: An Organizing Review

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