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When library users wish to know more about a book before actually reading it, or simply want to learn what others who have read a book think about it, they have at their disposal a well established body of book review literature. Since these reviews are scattered throughout the periodical media, there has long been a need for a tertiary medium that indexes the reviews in periodicals. The Book Review Digest (BRD), published by the H.W. Wilson Company, had been the sole source of citations to book reviews for a relatively general public until 1965 when Gale Research Company commenced publication of Book Review Index (BRI). Current Book Review Citations (CBRC), also published by the H.W. Wilson Company, joined the field in 1976. Other more subject‐specific book review indexes are currently available. The need for these specialized indexes in any particular library can easily be determined by the special needs of the library's clientele.

The selection of materials for library collections serving children remains heavily dependent on reviews for the identification and evaluation of appropriate items. It is desirable, therefore, that librarians and others who select juvenile books have access to reviews of all titles recently published (although one hundred percent coverage may never actually be possible), that this access be prompt, and that the content of reviews be helpful. That is, the review should describe the book sufficiently for the selector to decide on its usefulness for his/her purposes, and should evaluate the title with authority.

The British scholar S.C. Bradford first showed that the dispersion of periodical articles on a subject follows a predictable pattern. Based on his study of the literature of applied geology and lubrication, Bradford observed that:

Industry platforms can alter relations among exchange partners in such a way that the industry structure is changed. The focus of much industry platform research has been on how platform creation and leadership offers advantages to the most central firms, but platforms can also be advantageous for small specialist firms that compete with the most central firms. We examine book publishing as an example of an industry in which the central players – large publishing firms – are losing power to self-publishing authors because the distributor Amazon has a powerful platform for customers to communicate independently, and the non-publishing platform Twitter also serves as a medium for readers to discuss and review books. Our empirical analysis is based on downloaded sales statistics for Amazon Ebooks, matched with Amazon reviews of the same books and tweets that refer to the book or the author. We analyze how Ebook sales are a function of publisher, Amazon reviews, and tweets, and we are able to assess the importance of each factor in the sale of book titles. The main finding is that Amazon reviews are powerful drivers of book sales, and have greater effect on the sales of books that are not backed by publishers. Twitter also affects book sales, but less strongly than Amazon reviews.

The role of everyday citizens in the production of knowledge has become central to the study of media sociology. This interest is fueled by the growth of information communication technologies that have made it easier for amateurs to produce and disseminate content. The world of book reviewing – an exemplar of a field transformed by digitalization – concerns about the rise of amateurs manifests in the grievance that, “Nowadays, everyone’s a critic.” This chapter empirically investigates this idea by asking: Who is qualified to be a reviewer? The chapter draws on in-depth interviews with review editors, critics, and bloggers who have successfully crossed over to publish in some of the most important outlets in the English-publishing field. Analysis reveals that openness is central to ideas of what qualifies someone to be a book reviewer and how reviewers subsequently get work. Openness, however, is an example of noncertifiable skills, which are ascertained primarily through informal methods such as turning toward one’s personal and professional networks for recommendations from peers or relying on personal face-to-face encounters. A practical consequence of this selection criterion is that only reviewers who are known to book review editors in this specific way (i.e., their tastes and esthetic openness) are eligible candidates for professional review assignments. In this way, the commitment to openness as a professional value among book reviewers actually operates as a mechanism of closing their occupational boundaries.

The authors’ goal is to investigate variations in the writing style of book reviews published on different social reading platforms and referring to books of different genres, which enables acquiring insights into communication strategies adopted by readers to share their reading experiences.

The authors propose a corpus-based study focused on the analysis of A Good Review, a novel corpus of online book reviews written in Italian, posted on Amazon and Goodreads, and covering six literary fiction genres. The authors rely on stylometric analysis to explore the linguistic properties and lexicon of reviews and the authors conducted automatic classification experiments using multiple approaches and feature configurations to predict either the review's platform or the literary genre.

The analysis of user-generated reviews demonstrates that language is a quite variable dimension across reading platforms, but not as much across book genres. The classification experiments revealed that features modelling the syntactic structure of the sentence are reliable proxies for discerning Amazon and Goodreads reviews, whereas lexical information showed a higher predictive role for automatically discriminating the genre.

The high availability of cultural products makes information services necessary to help users navigate these resources and acquire information from unstructured data. This study contributes to a better understanding of the linguistic characteristics of user-generated book reviews, which can support the development of linguistically-informed recommendation services. Additionally, the authors release a novel corpus of online book reviews meant to support the reproducibility and advancements of the research.

The purpose of this study is to investigate how book group recommendations can be used as a meaningful way to suggest suitable books to users, given the increasing number of individuals engaging in sharing and discussing books on the web.

The authors propose reviews fine-grained classification (CFGC) and its related models such as CFGC1 for book group recommendation. These models can categorize reviews successively by function and role. Constructing the BERT-BiLSTM model to classify the reviews by function. The frequency characteristics of the reviews are mined by word frequency analysis, and the relationship between reviews and total book score is mined by correlation analysis. Then, the reviews are classified into three roles: celebrity, general and passerby. Finally, the authors can form user groups, mine group features and combine group features with book fine-grained ratings to make book group recommendations.

Overall, the best recommendations are made by Synopsis comments, with the accuracy, recall, F-value and Hellinger distance of 52.9%, 60.0%, 56.3% and 0.163, respectively. The F1 index of the recommendations based on the author and the writing comments is improved by 2.5% and 0.4%, respectively, compared to the Synopsis comments.

Previous studies on book recommendation often recommend relevant books for users by mining the similarity between books, so the set of book recommendations recommended to users, especially to groups, always focuses on the few types. The proposed method can effectively ensure the diversity of recommendations by mining users’ tendency to different review attributes of books and recommending books for the groups. In addition, this study also investigates which types of reviews should be used to make book recommendations when targeting groups with specific tendencies.

In recent years, readers have limited amounts of time to pick the right books to read from a market that is filled with similar types of books. Aiming to read only good books, readers tend to check book reviews written by others. However, it is very difficult to find good book reviews. The aim of this paper is to present a book review recommendation system that collects reviews from heterogeneous sources on the Internet and performs quality judgments automatically. Users can then read the top‐ranked reviews suggested by this recommendation system.

In this paper, a book review recommendation system is constructed to collect, process, and judge the quality of book reviews from various heterogeneous sources. The quality measurement of book reviews uses review‐evaluation techniques. The prediction results were validated with a ranking list produced by experts.

The proposed system is effective and suitable for recommending quality book reviews from heterogeneous sources. The proposed quality measurement method is more effective than other more commonly used methods.

This paper is one of the first to apply review evaluation techniques to the process of book review recommendation. The proposed system can collect and recognize book reviews from different websites with various forms of presentation. This evaluation shows that the quality measurement method produces better results than do other methods, such as ranking by rating score or by the date that the review was posted. Those methods are primarily used by commercial websites.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.