Nikolaos Korfiatis

Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content

Online reviews have received much attention recently in the literature, as their visibility has been proven to play an important role during the purchase process. Furthermore, recent theoretical insight argue that the votes casted on how helpful an online review is (review helpfulness) are of particular importance, since they constitute a focal point for examining consumer decision making during the purchase process. In this paper, we explore the interplay between online review helpfulness, rating score and the qualitative characteristics of the review text as measured by readability tests. We construct a theoretical model based on three elements: conformity, understandability and expressiveness and we investigate the directional relationship between the qualitative characteristics of the review text, review helpfulness and the impact of review helpfulness on the review score. Furthermore, we examine whether this relation holds for extreme and moderate review scores. To validate this model we applied four basic readability measures to a dataset containing 37,221 reviews collected from Amazon UK, in order to determine the relationship between the percentage of helpful votes awarded to a review and the review texts stylistic elements. We also investigated the interrelationships between extremely helpful and unhelpful reviews, as well as absolutely positive and negative reviews using intergroup comparisons. We found that review readability had a greater effect on the helpfulness ratio of a review than its length; in addition, extremely helpful reviews received a higher score than those considered less helpful. The present study contributes to the ever growing literature on on-line reviews by showing that readability tests demonstrate a directional relationship with average length reviews and their helpfulness and that this relationship holds both for moderate and extreme review scores.

The Impact of Readability on the Usefulness of Online Product Reviews: A Case Study on an Online Bookstore

Online product reviews is an important advantage for consumers of experience goods in online marketplaces and act as a useful source of information during the purchase of a good. Furthermore in some online marketplaces consumers have the opportunity to evaluate how helpful a review was by using a binary evaluation interface provided by the online marketplace. This results to the usefulness score of a review which is calculated as a fraction of helpful votes over the total votes that this review has received. Our early results indicate that the usefulness score of a particular review is affected in a significant way by the qualitative characteristics of the review as measured by readability tests applied to a large dataset of reviews collected from the UK section of the popular online marketplace Amazon.

Music, musicians and information seeking behaviour

Purpose – The purpose of this paper is to examine information seeking behaviour targeted to music information seeking by amateur musicians, accompanied with empirical evidence from a survey on a community concert band. While several studies in the literature have examined information seeking in the context of hedonic motives (e.g. entertainment oriented), music information can also be used for utilitarian purposes by providing amateur musicians the necessary tools to improve their skill and become better in their practice. Design/methodology/approach – A review of the literature on music information seeking and an empirical study on members of an amateur concert band are presented. The theoretical construct of the survey is informed by Wilsons’ macro model of information seeking behaviour. This is employed in order to understand information motives and needs, as well as obstacles in information seeking of musicians. Findings – Musicians seek information not only for entertainment but for educational purpo...

Using Online Consumer Reviews as a Source for Demographic Recommendations: A Case Study Using Online Travel Reviews

Online consumer reviews play an important role in the decision to purchase services online, mainly due to the rich information source they provide to consumers in terms of evaluating “experience”-type products and services that can be booked using the Internet, with online travel services being a significant example. However, different types of travelers assess each quality indicator differently, depending on the type of travel they engage in, and not necessarily their cultural or age background (e.g. solo travelers, young couples with children etc.). In this study, we present architecture for a demographic recommendation system, based on a user-defined hierarchy of service quality indicator importance, and classification of traveler types. We use an algebraic approach to ascertain preferences from a large dataset that we obtained from the popular travel website Booking.com using a web crawler and compared with the customer-constructed preference matrix. Interestingly, the architecture of the evaluated recommendation system takes into account already defined demand characteristics of the hotels (such as the number of reviews of specific consumer types compared to the total number of reviews) in order to provide an example architecture for a recommendation system based on user-defined preference criteria.

You Scratch Someone's Back and We'll Scratch Yours: Collective Reciprocity in Social Q&A Communities

Taking a structuration perspective and integrating reciprocity research in economics, this study examines the dynamics of reciprocal interactions in social question & answer communities. We postulate that individual users of social Q&A constantly adjust their kindness in the direction of the observed benefit and effort of others. Collective reciprocity emerges from this pattern of conditional strategy of reciprocation and helps form a structure that guides the very interactions that give birth to the structure. Based on a large sample of data from Yahoo! Answers, our empirical analysis supports the collective reciprocity premise, showing that the more effort (relative to benefit) an asker contributes to the community, the more likely the community will return the favor. On the other hand, the more benefit (relative to effort) the asker takes from the community, the less likely the community will cooperate in terms of providing answers. We conclude that a structuration view of reciprocity sheds light on the duality of social norms in online communities.

Examining Patterns of Information Behavior Among Healthcare Professionals: A Case Study on Health Psychologists

Psychologists are an understudied population in terms of information needs and information seeking behavior. This article provides theoretical analysis accompanied with some empirical evidence drawn from a nationwide survey of psychologists working in the Greek National Healthcare System (GNHS). The empirical study was conducted during the spring of 2011, through a specially designed questionnaire distributed to all psychologists within GNHS. Psychologists seek information for patient consultation purposes and for knowledge updating; they prefer using their personal library, internet search engines, and their colleagues as information sources, while the main obstacles they face include the lack of hospital libraries. This research identified the need to more strongly link hospital library services to health psychologists on the grounds of their information needs and behaviors.

Social Measures and Flexible Navigation on Online Contact Networks

This paper discusses ways of navigating online contact networks -networks of social connections defined under a relational context -on a way that can provide more meaningful information to those that use them. We use the concept of social distance to address the different levels of social information and express the subjective vagueness in social ties by means of fuzzy numbers. The implementation of an algorithm for measuring prestige based on such vague estimations is reported. For the sake of illustration, a numerical example using a fuzzy graph is provided in which the strength or weakness of the connections is defined as a fuzzy number.

Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology

Abstract Consumer adoption of mobile shopping apps is an emerging area in m-commerce which poses an interesting challenge for retailers and app developers. In this study, we adapt the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to investigate factors predicting consumer behavioral intention (BI) and use behavior (UB) towards mobile shopping apps, considering the impact of two manifestations of consumers perceived risk: Privacy Risk and Security Risk. Because cultural characteristics may moderate the impact of these risks on behavioral intention and use behavior, we conduct two studies from two consumer panels from countries with significant difference in technology use as captured by the Computer-Based Media Support Index (CMSI), namely India (high CMSI) and USA (low CMSI). For both countries, the baseline UTAUT 2 constructs predict the Behavioral Intention to use mobile shopping apps (and subsequently use behavior). However, the manifestations of perceived risk are significant only for the country with the highest CMSI score, suggesting that cultural influences play a strong role in the adoption of m-shopping. Our study has practical implications for theory as it poses the use of m-shopping apps in a cross-cultural context, suggesting that privacy and security moderate intention to use differently across cultures as predicted by the CMSI. From that perspective, it also has practical implications for consumer behavior researchers and app developers challenged with app localization as well as retailers designing mobile shopping apps for an intercultural audience.

Setting Up a Big Data Project: Challenges, Opportunities, Technologies and Optimization

In the first part of this chapter we illustrate how a big data project can be set up and optimized. We explain the general value of big data analytics for the enterprise and how value can be derived by analyzing big data. We go on to introduce the characteristics of big data projects and how such projects can be set up, optimized and managed. Two exemplary real word use cases of big data projects are described at the end of the first part. To be able to choose the optimal big data tools for given requirements, the relevant technologies for handling big data are outlined in the second part of this chapter. This part includes technologies such as NoSQL and NewSQL systems, in-memory databases, analytical platforms and Hadoop based solutions. Finally, the chapter is concluded with an overview over big data benchmarks that allow for performance optimization and evaluation of big data technologies. Especially with the new big data applications, there are requirements that make the platforms more complex and more heterogeneous. The relevant benchmarks designed for big data technologies are categorized in the last part.

Social metadata for the impact factor

– The purpose of this research is to address the need for a definition of metadata descriptors for use in enhancing the accuracy of bibliometric instruments of scholarly evaluation, such as the impact factor., – A semantic vocabulary – COAP – is constructed, deployed on top of the Resource Description Framework (RDF), by extending the Friend‐of‐a‐Friend (FOAF) schema., – An extension of the FOAF vocabulary is considered as the ability to describe a publication record such as this paper in terms of scholar contributions and participations. In order to achieve that, the FOAF vocabulary is extended., – The application of this semantic vocabulary could be used as a way of enhancing the accuracy of source data for bibliometric evaluation instruments., – The paper discusses how metadata descriptors can contribute to the improvement of already established scholar evaluation instruments such as the impact factor. It will be of use in the development of digital libraries.