THE EFFECT OF FLUENCY ON REVIEW HELPFULNESS: DOES IT DEPEND ON PERSPECTIVE-TAKING?

In this paper, we propose to explore the effects of fluency and perspective-taking on the perceived helpfulness of online product reviews. Past research has suggested that fluency, or ease of information processing, can be used as information when individuals are making various judgments. For example, fluency increases liking. Thus, we predict that fluency can influence perceptions of review helpfulness. Moreover, researchers have found that social distance, or the distinction between self and other, can affect judgment. Specifically, taking other-perspective can reduce feelings in response to disfluency. Therefore, we further predict that a review presented in fluent information will be perceived as more helpful than one in disfluent information when individuals consider a product for themselves, but not when they imagine that another person will purchase the product. To test the theoretical model proposed, we will present a book review in easy- and hard-to-read fonts in Study 1, and prepare another review in high- and low-contrast texts in Study 2. Participants will be instructed to take self- or other-perspective when rating review helpfulness. Our results will indicate the important roles of fluency and perspective-taking in consumer evaluation of online product reviews and provide implications for consumers and online retailers

What Makes a Helpful Online Review When Information Overload Exists?

With the increasing of online reviews, information overload has become a major problem in online community. What makes a helpful online review when information overload exists? In this study, the research model is developed to examine the helpfulness of online consumer reviews when information overload exists. Information quality is measured by review length and pictures in the model. The result is showed the relationship between review length and review helpfulness is usually described as an inverted U curve. The impact of review length and picture review on helpfulness is stronger when information overload exists. The impact of is also stronger with negative reviews than without negative reviews. As a result, our findings help extend the literature on information diagnosticity within the context of information overload

How Does the Authenticity in an Online Review Affect Its Helpfulness? A Decision Tree Induction Theory Development Approach

Drawing on multi-dimensionality of authenticity, this study focuses on the role of two distinct authenticities: nominal and expressive. We propose that the type of authenticity in a review will vary based on the reviews’ lexical density (word level) and breadth (sentence level). Using the decision tree induction approach, the main and interaction effects of the dimensions and forms of authenticity are examined for their effect on review helpfulness. The preliminary analysis of 470 reviews demonstrate that the lexical density form of expressive authenticity is a predominant predictor of online review helpfulness. Additionally, the effects of expressive authenticity depth, nominal authenticity breadth and depth on online review helpfulness, vary based on the expressive breadth. The decision tree induction approach provides new theoretical insights that extends the frontiers of authenticity and practical implications on online review helpfulness

Application of Penalized Logistic Regression Models in Text Classification

随着互联网科技的迅猛发展，人类社会所记录的信息呈现“指数级”的增长。海量信息的快速准确分类、查询及个性化推荐等，有着非常迫切的需求。为了更好地解决文本分类任务中的高维稀疏数据分类问题，本文主要做了以下研究工作。 首先，对文本分类各流程所涉及的技术进行了全面的梳理，以准确把握文本分类亟需突破的难点。接着，对惩罚Logistic模型进行了理论发展概述；同时，从文献综述的角度探讨了惩罚Logistic模型在解决文本分类问题中的可行性，并结合词向量理论和惩罚Logistic模型提出一种新的文本分类算法。然后，为了验证惩罚Logistic模型在特征选择和分类准确率两方面的能力，将多种惩罚Logis...With the rapid development of Internet technology, the information in human society increases exponentially. Fast and accurately classification and recommendation of text information are in great demand. In order to solve the high dimension and sparse data problem faced by the text classification task, our paper mainly do the following research work. Firstly, we carry out a comprehensive introd...学位：应用统计硕士院系专业：经济学院_应用统计硕士学号：1542014115197

How is the review helpfulness evaluated?

A user-generated review that is perceived as helpful is valuable for both customer and the retailer, and that is why online markets such as Amazon.com collect public opinion on reviews that are perceived more helpful. Review platforms allow customers to vote for reviews they deem helpful. While prior literature has examined what drives the helpfulness of reviews, many of these studies have looked at drivers of perceived helpfulness of reviews in isolation. Using the lens of dual process theory, this research examines how consumers evaluate the helpfulness of a review. We propose a framework and provide empirical evidence for the evaluation of the review helpfulness process. We find that extreme reviews have a higher effect on review helpfulness compared to moderate reviews, and this effect is mediated by the depth and sentiment of the review content

When More is More and Less is More: Depth and Breadth of Product Reviews and Their Effects on Review Helpfulness

With the growth of online shopping coupled with mobile technology, user-generated product reviews have become an important source of information for product diagnosticity. A significant academic endeavor has been made to comprehend what information factors of reviews help prospective customers better diagnose products. One such factor is review depth that is estimated by the number of a review’s words. We propose review breadth as an additional factor based on a review’s number of topics—the more review breadth, the more diverse information. By conducting the statistical and predictive analyses, we demonstrate that review breadth reliably measures a review’s information. This study makes academic and practical contributions. For academic researchers, review breadth is worth considering as a factor to estimate a review’s information over and above review depth. Based on the two information factors of review breadth and review depth, practitioners can recommend more helpful product reviews to their prospective customers

Cross-Cultural Examination on Content Bias and Helpfulness of Online Reviews: Sentiment Balance at the Aspect Level for a Subjective Good

Online reviews can be fraught with biases, especially on experience goods. Using multilingual sentiment analysis software, we examined the characteristics of review biases and helpfulness at the aspect level across two different cultures. First, we found the lopsidedness of emotions expressed over the four key aspects of Japanese restaurant reviews between Japanese and Western consumers. Second, helpful reviews have sentiments expressed more evenly over those aspects than average for both Japanese and Western consumers. Third, however, there are significant differences over how sentiments are spread over aspects between them. Westerners found reviews helpful when reviews focused less on food and more on service. In addition, Japanese customers were more concerned with savings whereas Westerners paid attention to whether they are getting their money’s worth. These findings point to future research opportunities for leveraging sentiment analysis over key aspects of goods, particularly those of experience/subjective goods, across different cultures and customer profile categories

HETEROGENEOUS GRAPH-BASED USER-SPECIFIC REVIEW HELPFULNESS PREDICTION

With the popularity of e-commerce and review websites, it is becoming increasingly important to identify the helpfulness of reviews. However, existing works on predicting reviews’ helpfulness have three major issues: (i) the correlation between helpfulness and features from review text is not clear yet, although many standard features are proposed, (ii) the relations between users, reviews and products have not been considered, (iii) the effectiveness of the existing approaches have not been systematically compared. To address these challenges, we first analyze the correlation between standard features and review helpfulness that are widely used in other work. Based on this analysis, we propose an end-to-end neural network architecture, the Global-Local Heterogeneous Graph Neural Networks (GL-HGNN). It consists of the graph construction and learning nodes representations both globally and locally. The graph is composed of three types of nodes including users, reviews and products, as well as four link types to build connections among these nodes. To better learn the feature representations, we employ a global graph neural network (GNN) branch and a local GNN branch on the whole graph and associated subgraphs to capture graph structure and information propagation. Finally, we provide an empirical comparison with traditional machine learning models training on hand-crafted features as well as four state-of-the-art deep learning models on eight Amazon product categories

The Influence of Visual Social Media, Online Customer Reviews, and Personal Communication on Young Adults’ Purchase Intention: A Mixed Methods View into Consumer Socialization

Due to an increase in visually-oriented online social media websites and other user-generated content, such as online customer reviews, young adults are learning and using consumer-related knowledge differently than in the past. Traditionally, individuals emulated their consumption style after behaviors modeled by family, peers, and traditional forms of mass media.  Since the popularity of visual social media and online customer reviews have gained a stronghold on young adults, it was hypothesized that individuals gain consumer knowledge of products through visual social media and other user-generated customer reviews. Explanatory sequential mixed methods were used to investigate which resources young adult consumers consult when searching for product information. Survey results indicate that young adults rely on visual social media and online customer reviews for information about products. Family members and peers were consulted for products as well, with findings from individual interviews indicating that mothers were the most influential resource. Keywords: Consumer socialization; Online customer reviews; Visual social networking website

Peran Mediasi Kepercayaan dan Kesadaran Merek pada Pengaruh antara Ulasan Pelanggan Online terhadap Niat Pembelian (Study pada Pengguna E-Commerce)

Online Customer Review merupakan inti dari strategi pemasaran kontemporer. Namun, hingga saat ini, hanya sedikit perhatian yang diberikan untuk mengembangkan ukuran ulasan online yang valid. Beberapa penelitian akademis telah menggunakan pendekatan untuk menjelaskan Online Customer Review, namun penelitian sebelumnya menunjukkan hasil yang inkonsisten. Beberapa penelitian menyatakan bahwa Online Customer Review berpengaruh terhadap purchase intention, namun beberapa penelitian lainnya menunjukkan tidak adanya pengaruh dari online customer review terhadap purchase intention. oleh karena itu perlu dilakukan penelitian untuk menjelaskan perbedaan hasil penelitian dengan menempatkan kepercayaan dan brand awareness sebagai variabel mediasi. Berdasarkan pengendalian variabelnya penelitian ini merupakan pengendalian survei, Populasi dalam penelitian ini adalah pengguna e-commerce yang ada diindonesia. Jumlah total responden pada penelitian ini adalah 304 orang. Alat analisis pada penelitian ini menggunakan pendekatan Partial Least Square (PLS) dengan bantuan menggunakan perangkat lunak SmartPLS. Berdasarkan hasil analisis data diperoleh simpulan bahwa : (1) Contextual Image dan Numerical Rating menjadi faktor penentu penting dalam niat pembelian sebagai dimensi dari Online Customer Review, kecuali textual comment. (2) Kepercayaan memediasi dari pengaruh online customer review pada niat pembelian, kecuali pada dimensi Contextual image. (3) Brand awareness memediasi dari pengaruh online customer review terhadap niat pembelian. Rekomendasi kedepannya dapat memperluas sampel penelitian seperti perbedaan antar generasi dan pengelompokkan jenis produk tertentu untuk membandingkan peran online customer review terhadap niat pembelian