• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Science of Emotion and Sensibility
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• v.21 no.4
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• pp.25-36
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• 2018

Nowadays, it is hard to imagine one's life without smart phones or the internet. Furthermore, not only do people form groups offline, but also online. Based on the cognitive dissonance theory, there have been many studies about how an offline group's initiation affects attitudes toward the group. However, there has not been a study about how an online group's initiation can affect attitudes toward the group. Therefore, this study aims to find out how cognitive dissonance aroused by initiation affects the attitudes toward the online community, which represents groups that are formed online. In addition, this study examined how perceived similarity affects changes in attitude aroused by cognitive dissonance. Participants were assigned to a group in three ways as follows: without a registration process, with a simple registration process, and/or with a complex registration process. Perceived similarity was calculated by the difference between the current body mass index (BMI) and the target BMI of the participant. Attitudes toward the online group were measured by perceived source credibility, perceived information quality, satisfaction, information usefulness, and continuance intention. Contrary to the cognitive dissonance theory, the results showed that when applied to offline social groups, there were conflicting results. There were cases where there was no difference in the evaluation between initiation conditions. However, other cases showed that groups with the most complex registration process were found to have the worst evaluation. People were more favorable toward the group when the perceived similarity was larger. Interestingly, people who had higher perceived similarity had more positive attitudes toward the groups that had been assigned with a registration process compared to the group formed without a registration process. Conversely, people with lower perceived similarity had more positive attitudes toward the group when there was no initiation process. Online communities may use the results of this study to design more suitable registration processes for their communities.