The impact of emotions on the helpfulness of movie reviews

Improving Graph-Based Movie Recommender System Using Cinematic Experience

With the advent of many movie content platforms, users face a flood of content and consequent difficulties in selecting appropriate movie titles. Although much research has been conducted in developing effective recommender systems to provide personalized recommendations based on customers’ past preferences and behaviors, not much attention has been paid to leveraging users’ sentiments and emotions together. In this study, we built a new graph-based movie recommender system that utilized sentiment and emotion information along with user ratings, and evaluated its performance in comparison to well known conventional models and state-of-the-art graph-based models. The sentiment and emotion information were extracted using fine-tuned BERT. We used a Kaggle dataset created by crawling movies’ meta-data and review data from the Rotten Tomatoes website and Amazon product data. The study results show that the proposed IGMC-based models coupled with emotion and sentiment are superior over the compared models. The findings highlight the significance of using sentiment and emotion information in relation to movie recommendation.

The interpersonal effects of distinct emotions in online reviews

Emotional expressions in online reviews affect reviews' informative value. By comparing high and low arousal emotions with a negative and positive valence, the current research demonstrates that the effects of emotional expressions in online reviews are determined not by the level of arousal, but by the perceived rationality of the reviewer and the perceived appropriateness of the emotional expression. In a lab experiment (N = 242) among university students, and an online experiment (N = 252) on Prolific Academic involving native English speakers, participants read an online restaurant review with the negative emotions anger, disappointment, or disgust, or with the positive emotions happiness, excitement, or contentment. Results showed that readers of online reviews considered expressions of anger more inappropriate than expressions of disappointment or disgust; this led them to judge the reviewer as more irrational, which decreased the informative value of the review. As a consequence, angry reviews led to less negative restaurant evaluations and stronger intentions to visit the restaurant than reviews expressing disappointment or disgust. We found no differences between contentment and happiness (Study 1), or between contentment and excitement (Study 2). Our findings underscore the importance of studying the effects of discrete emotions in online reviews.

Deep learning and multimodal target recognition of complex and ambiguous words in automated English learning system

On the basis of convolution neural network, deep learning algorithm can make the convolution layer convolute the input image to complete the hierarchical expression of feature information, which makes pattern recognition more simple and accurate. Now, in the theory of multimodal discourse analysis, the nonverbal features in communication are studied as a symbol system similar to language. In this paper, the author analyzes the deep learning complexity and multimodal target recognition application in English education system. Multimodal teaching gradually has its practical significance in the process of rich teaching resources. The large-scale application of multimedia technology in college English classroom is conducive to the construction of a real language environment. The simulation results show that the multi-layer and one-dimensional convolution structure of the product neural network can effectively complete many natural language problems, including the tagging of lexical and semantic roles, and thus effectively improve the accuracy of natural language processing. Multimodal teaching mode helps to memorize vocabulary images more deeply. 84% of students think that multi-modal teaching mode is closer to life. Meanwhile, multimedia teaching display is more acceptable. College English teachers should renew their teaching concepts and adapt themselves to the new teaching mode.

What makes a helpful online review? Empirical evidence on the effects of review and reviewer characteristics

Purpose

The reviews submitted by users are the foundation of user-generated content (UGC) platforms. However, the rapid growth of users brings the problems of information overload and spotty content, which makes it necessary for UGC platforms to screen out reviews that are really helpful to users. The authors put forward in this paper the factors influencing review helpfulness voting from the perspective of review characteristics and reviewer characteristics.

Design/methodology/approach

This study uses 8,953 reviews from 20 movies listed on Douban.com with variables focusing on review characteristics and reviewer characteristics that affect review helpfulness. To verify the six hypotheses proposed in the study, Stata 14 was used to perform tobit regression.

Findings

Findings show that review helpfulness is significantly influenced by the length, valence, timeliness and deviation rating of the reviews. The results also underlie that a review submitted by a reviewer who has more followers and experience is more affected by review characteristics.

Originality/value

Previous literature has discussed the factors that affect the helpfulness of reviews; however, the authors have established a new model that explores more comprehensive review characteristics and the moderating effect reviewer characteristics have on helpfulness. In this empirical research, the authors selected a UGC community in China as the research object. The UGC community may encourage users to write more helpful reviews by highlighting the characteristics of users. Users in return can use this to establish his/her image in the community. Future research can explore more variables related to users.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2020-0186.

The Joint Influence of Online Rating and Product Price on Purchase Decision: An EEG Study

Background

Consumers had to encounter and consider product-oriented and review-oriented cues before making an online purchasing decision. It was important to resolve how these cues influenced consumers’ online purchasing decision. We also knew little about how the human brain processed these cues simultaneously, and which cue would occupy a dominant position in neural activity. The purpose of the present study was to investigate the neural correlates of online shopping decisions and how online rating and product price jointly influenced such purchase decisions.

Research Method

Eighteen undergraduates were recruited to participate in this research. Each participant was exposed to all four experimental conditions combining 2 (product price: high vs. low) × 2 (online rating: positive vs. negative) with a total of 192 trials. They were required to rate the degree of willingness-to-pay. EEG data were obtained with 64 electrodes placed on the Easy Cap according to the International 10–20 system. We conducted both the event-related potentials analysis and the time-frequency analysis for the EEG data.

Results

The behavioral findings indicated that products with positive rating and low price increased the willingness-to-pay. The EEG results showed that larger late positive potentials were elicited by products with low price compared with high price under positive rating condition, but not under negative rating condition, reflecting the modulated effect of online rating on the emotional arousal elicited by product price. Furthermore, we found larger alpha event related desynchronization elicited by products with positive rating compared with negative rating, indicating that more cognitive resources were allocated for products with a positive rating.

Conclusion

Combined with behavioral and EEG analysis, our results emphasized the more important position of product rating compared with price. The findings deepened the understanding of the neural mechanisms underlying the online shopping decision process. More attention should be paid to online ratings on the webpage of the electronic store, because negative ratings made a product less appealing for prospective consumers regardless of price. Thus, the owners should build good reputations for their online products, which were fundamental to the consumers’ online purchasing decisions.

Finding “just right” books for children: analyzing sentiments in online book reviews

Purpose

This study is part of a larger research project which aims to investigate whether sentiments in online reviews on children’s books would represent significant factors which are useful for selecting the right books for children. This paper aims to examine whether positive, negative or neutral attitude would be directly associated with the overall ratings of books.

Design/methodology/approach

The study investigates subjectivity and polarity of online reviews on children’s books such as neutral, positive or negative sentiment. For the investigation of a statistical association between the sentiment values and the rating scores, this study performs correlation analysis. For a clear explanation of the factors affecting the relationships between the sentiment value and the rating score, this study uses the concept-level sentiment analysis of online reviews.

Findings

The findings of this study demonstrate that there is a weak or low correlation between the sentiment value and the rating score of a book and they are hardly related for most books. The results of this study also uncover key contributing factors that affected the correlations between two variables and made the relationship weak.

Research limitations/implications

This study increases awareness of the implications of online reviews as user-generated contents for complementing the existing controlled vocabulary.

Practical implications

This study contributes to improving library catalogs by using latent topics extracted from online reviews which provide additional access points for assisting in the selection of books.

Originality/value

Although several studies have conducted on online reviews in the domain of business, no research appears to exist on the sentiment analysis of online reviews about children’s books. This study attempts to address the potential and challenges associated with using online reviews to help find the right books for children.