AN APPROACH FOR REVIEWING AND RANKING THE CUSTOMERS’ REVIEWS THROUGH QUALITY OF REVIEW (QoR)

Kawate, Sumit; Patil, Kailas

doi:10.21917/ijsc.2017.0193

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…Sentimentr has mostly been applied by computer scientists in studying big data, such as consumers' online reviews (Kawate & Patil, 2017), emotion that YouTubers convey (Kleinberg, Mozes, & van der Vegt, 2018), and online polls (Kassraie, Modirshanechi, & Aghajan, 2017). Although sentimentr has not been used in mainstream psychology, it has been applied to many areas of research involving the study of emotion, such as public opinions in business and management (Ikoro, Sharmina, Malik, & Batista-Navarro, 2018;Sinha, Choudhury, & Agrawal, 2014), political science (Sanders, 2018) and even predicting stock trend from sentiments reflected in the market and social media (J.…”

Section: Sentimentrmentioning

confidence: 99%

Application of sentence-level text analysis: The role of emotion in an experimental learning intervention

Man-yu

2022

Journal of Experimental Social Psychology

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This registered study aimed at testing the role of emotion in the intervention effect of an experimental intervention study in academic settings. Previous analyses of the National Study of the Learning Mindset (Yeager et al., 2019) showed that in a randomized controlled trial, high school students who were given the growth mindset intervention had, on average higher GPA than did students in the control condition. Previous analyses also showed that school achievement levels moderated the intervention effect. This study applied a sentence-level text analysis strategy to detect participants' attentional focus in five emotional dimensions (valence, arousal, dominance/control, approach-avoidant, and uncertainty) across three writing prompts students wrote during the intervention. Linear mixed models were conducted to test if emotional dimension scores computed using the text analysis predicted a higher intervention effect (i.e., higher post-intervention GPA given pre-intervention GPA). The moderating role of school achievement levels was also examined. The results of this study have implications on the possibility of applying text analysis strategies on open-ended questions in interventions or experimental studies to examine the role of the emotion-attentional focus of participants during intervention or experimental studies on the intervention or experimental outcomes, especially those that are conducted in academic settings.

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Section: Sentimentrmentioning

confidence: 99%

Application of sentence-level text analysis: The role of emotion in an experimental learning intervention

Man-yu

2022

Journal of Experimental Social Psychology

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“…Another score that appears alongside the review helpfulness score, the review unhelpfulness score, has attracted significantly less attention from researchers. This score is usually used as another factor that represents review characteristics to perform several operations such as detecting review spams [26] and ranking reviews [27]. In the meantime, the most popular usage of the review unhelpfulness score in the literature is to use it as a discount factor when measuring review quality through the review helpfulness score.…”

Section: Review Unhelpfulness Scorementioning

confidence: 99%

Are Review Helpfulness Score and Review Unhelpfulness Score Two Sides of The Same Coin or Different Coins?

Khern-am-nuai¹,

Yu²

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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Online review platforms have increasingly incorporated the review evaluating system (i.e., a system that allows users to evaluate whether reviews are helpful/unhelpful) to assist review readers and encourage review contributors. However, although we have extensive knowledge about the review helpfulness score, our insights regarding its counterpart, the review unhelpfulness score, are lacking. Addressing this limitation is important because many researchers have adopted the review unhelpfulness score assuming that it is driven by intrinsic review characteristics while practitioners also implicitly assume that the unhelpfulness score can identify low-quality reviews. The primary objective of this work is to verify whether the review unhelpfulness score is influenced by intrinsic review characteristics that drive review helpfulness score. We find that unlike review helpfulness score, unhelpfulness score is not driven by intrinsic review characteristics, and that helpfulness voters behave significantly different than unhelpfulness voters. Further implications and future directions are also discussed.

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“…Although researchers have studied review helpfulness scores extensively, review unhelpfulness scores have received far less attention. Notably, several studies have observed that review unhelpfulness scores help facilitate online review platforms' operations, such as review spam detecting [30] and review ranking [31]. Meanwhile, in one of the few studies that investigate the generation of review unhelpfulness scores, Connors, Mudambi and Schuff [13] use a controlled laboratory experiment to show factors that are correlated with review unhelpfulness scores; some of these factors are related to intrinsic review characteristics (e.g., "lack of information," "poor writing style"), whereas others are not as apparent (e.g., "low credibility").…”

Section: Review Unhelpfulness Scoresmentioning

confidence: 99%

Review Helpfulness Score vs. Review Unhelpfulness Score: Two Sides of the Same Coin or Different Coins?

Khern-am-nuai

Gutt

2021

SSRN Journal

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AN APPROACH FOR REVIEWING AND RANKING THE CUSTOMERS’ REVIEWS THROUGH QUALITY OF REVIEW (QoR)

Cited by 7 publications

References 16 publications

Application of sentence-level text analysis: The role of emotion in an experimental learning intervention

Application of sentence-level text analysis: The role of emotion in an experimental learning intervention

Are Review Helpfulness Score and Review Unhelpfulness Score Two Sides of The Same Coin or Different Coins?

Review Helpfulness Score vs. Review Unhelpfulness Score: Two Sides of the Same Coin or Different Coins?

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