scholarly journals The interpersonal effects of distinct emotions in online reviews

2021 ◽  
pp. 1-24
Author(s):  
Gert-Jan Lelieveld ◽  
Hanneke Hendriks
Keyword(s):  
Online Reviews ◽  
Interpersonal Effects

Anger in Consumer Reviews: Unhelpful but Persuasive?

MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1059-1086
Author(s):  
Dezhi Yin ◽  
◽  
Samuel Bond ◽  
Han Zhang ◽  
◽  
...  
Keyword(s):  
Laboratory Experiments ◽  
Online Communication ◽  
Consumer Attitudes ◽  
Online Reviews ◽  
Negative Influence ◽  
Purchase Decisions ◽  
Common Assumption ◽  
Consumer Reviews ◽  
Review Helpfulness ◽  
Interpersonal Effects

A common assumption in prior research and practice is that more helpful online reviews will exert a greater impact on consumer attitudes and purchase decisions. We suggest that this assumption may not hold for reviews expressing anger. Building on the theory of emotions as social information (EASI), we propose that although expressions of anger in a negative review tend to decrease reader perceptions of review helpfulness, the same expressions tend to increase the negative influence of the review on reader attitudes and decisions. Results from a series of laboratory experiments provide support for our claims. Our findings challenge the widely accepted assumption that more “helpful” reviews are ultimately more persuasive and extend the current understanding of the interpersonal effects of emotion in online communication. Our findings also suggest implications for review platforms, retailers, marketers, and manufacturers faced with the task of managing consumer reviews.

The Interdependence of Personality and Satisfaction in Couples

2016 ◽  
Vol 21 (4) ◽  
pp. 284-295 ◽  
Author(s):  
Rebekka Weidmann ◽  
Thomas Ledermann ◽  
Alexander Grob
Keyword(s):  
Relationship Satisfaction ◽  
Personality Traits ◽  
Big Five ◽  
Gender Effects ◽  
Big Five Traits ◽  
Personality Similarity ◽  
Interpersonal Effects

Abstract. Personality has been found to play an important role in predicting satisfaction in couples. This review presents dyadic research on the association between Big Five traits and both life and relationship satisfaction in couples focusing on self-reported personality, partner-perceived personality (how the partner rates one’s own personality), and personality similarity. Furthermore, special attention is given to possible gender effects. The findings indicate the importance of self-reported as well as partner-perceived reported personality for the satisfaction of both partners. Specifically, the majority of studies found intrapersonal and interpersonal effects for neuroticism, agreeableness, and conscientiousness on life or relationship satisfaction. For the partner-perceived personality, intrapersonal and interpersonal effects were present for all Big Five traits. Partners’ similarity in personality traits seems not to be related with their satisfaction when controlling for partners’ personality.

ANALYSING SENTIMENTS OF ONLINE REVIEWS ON RESTAURANTS IN MALAYSIA USING PREDICTIVE TEXT ANALYTICS

2018 ◽  
Vol 2018 ◽  
pp. 200-200
Author(s):  
Kok Wei Khong ◽  
◽  
Fon Sim Ong ◽  
Babajide AbuBakr Muritala ◽  
Ken Kyid Yeoh
Keyword(s):  
Online Reviews ◽  
Text Analytics

Management Responses to Online Reviews: Consumer Preferences of Action Frames and Language Style

2020 ◽  
Author(s):  
Agne Bendaraviciute ◽  
Philipp Wassler ◽  
Thi Hong Hai Nguyen ◽  
Simon Thomas
Keyword(s):  
Figurative Language ◽  
Consumer Preferences ◽  
Online Reviews ◽  
Theory And Practice ◽  
Discrete Choice Experiments ◽  
Hotel Management ◽  
Language Style ◽  
Multi Method Approach ◽  
Language Styles ◽  
Depth Interviews

This study was taken as the understanding of management responses remains scarcely understood in theory and practice, especially concerning consumer preferences. This study aims at examining consumer preferences of the action frames and language styles adopted in hotel management responses to online reviews. A multi-method approach, using discrete choice experiments followed by in-depth interviews, was employed. Findings show that past action frames in management responses are preferred by customers due to the certainty, trustworthiness and detailed information provided. Moreover, literal is favoured over figurative language style due to perceived professionalism and conciseness. The current study helps hotel management to further understand consumer preferences of management responses to online reviews, especially regarding action frames and language styles.

Inducing Consumer Online Reviews via Disclosure

2018 ◽  
Author(s):  
Xu Guan ◽  
Yulan Wang ◽  
Zelong Yi ◽  
Ying-Ju Chen
Keyword(s):  
Online Reviews

Herding, Learning and Incentives for Online Reviews

2020 ◽  
Author(s):  
Rajeev Kohli ◽  
Xiao Lei ◽  
Yeqing Zhou
Keyword(s):  
Online Reviews

Design of GA and Ontology based NLP Frameworks for Online Opinion Mining

2019 ◽  
Vol 13 (2) ◽  
pp. 159-165
Author(s):  
Manik Sharma ◽  
Gurvinder Singh ◽  
Rajinder Singh
Keyword(s):  
Genetic Algorithm ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Opinion Mining ◽  
Hybrid Genetic Algorithm ◽  
Online Reviews ◽  
Middle Tier ◽  
Complete Set ◽  
Mining Model

Background: For almost every domain, a tremendous degree of data is accessible in an online and offline mode. Billions of users are daily posting their views or opinions by using different online applications like WhatsApp, Facebook, Twitter, Blogs, Instagram etc. Objective: These reviews are constructive for the progress of the venture, civilization, state and even nation. However, this momentous amount of information is useful only if it is collectively and effectively mined. Methodology: Opinion mining is used to extract the thoughts, expression, emotions, critics, appraisal from the data posted by different persons. It is one of the prevailing research techniques that coalesce and employ the features from natural language processing. Here, an amalgamated approach has been employed to mine online reviews. Results: To improve the results of genetic algorithm based opining mining patent, here, a hybrid genetic algorithm and ontology based 3-tier natural language processing framework named GAO_NLP_OM has been designed. First tier is used for preprocessing and corrosion of the sentences. Middle tier is composed of genetic algorithm based searching module, ontology for English sentences, base words for the review, complete set of English words with item and their features. Genetic algorithm is used to expedite the polarity mining process. The last tier is liable for semantic, discourse and feature summarization. Furthermore, the use of ontology assists in progressing more accurate opinion mining model. Conclusion: GAO_NLP_OM is supposed to improve the performance of genetic algorithm based opinion mining patent. The amalgamation of genetic algorithm, ontology and natural language processing seems to produce fast and more precise results. The proposed framework is able to mine simple as well as compound sentences. However, affirmative preceded interrogative, hidden feature and mixed language sentences still be a challenge for the proposed framework.

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