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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 paper is to present an analysis of Goodreads’ user-generated book reviews from a linguistic perspective for insights into the psychological aspects of reviewers’ perceptions and behaviors. This examination of users’ language and perspectives may shed light on the role and value of user-generated reviews in complementing the traditional representation of resources and facilitating the discoverability of cultural objects.

This study involved a textual analysis of 474,803 unique reviews of Goodreads’ 2015 top-rated books generated by 9,335 Goodreads’ reviewers. In order to better understand the nuances of user-generated reviews, a content analysis was applied to 2,500 reviews of each of the five top-ranked titles in Goodreads’ Fiction Literature genre category.

The analysis of user-generated reviews demonstrates that language is a quite stable and reliable dimension across Goodreads’ users. The high rate of function words utilized, in particular I-words, coupled with positive emotion words, suggests that reviewers tended to convey their opinions in order to influence other individuals’ reading choices, or in Bourdieu’s (1985) terms, influence cultural production. In line with previous studies of user-generated reviews, the prevalence of positive reviews may also imply their unreliable nature. This study supports the importance of transparency regarding inclusion of user-generated reviews in traditional systems of knowledge representation, organization and discovery, such as WorldCat.

This study contributes to better understanding of linguistic characteristics of Goodreads’ reviews, including the role and value of user-generated reviews in complementing traditional representation of resources and facilitating discoverability of cultural objects.

The purpose of this paper is to assess the value of Goodreads reader ratings for measuring the wider impact of scholarly books published in the field of History.

Book titles were extracted from the reference lists of articles that appeared in 604 history journals indexed in Scopus (2007-2011). The titles were cleaned and matched with WorldCat.org (for publisher information) as well as Goodreads (for reader ratings) using an API. A set of 8,538 books was first filtered based on Dewey Decimal Classification class 900 “History and Geography”, then a subset of 997 books with the highest citations and reader ratings (i.e. top 25 per cent) was analysed separately based on additional characteristics.

A weak correlation (0.212) was found between citation counts and reader rating counts for the full data set (n=8,538). An additional correlation for the subset of 997 books indicated a similar weak correlation (0.190). Further correlations between citations, reader ratings, written reviews, and library holdings indicate that a reader rating on Goodreads was more likely to be given to a book held in an international library, including both public and academic libraries.

Research on altmetrics has focused almost exclusively on scientific journal articles appearing on social media services (e.g. Twitter, Facebook). In this paper we show the potential of Goodreads reader ratings to identify the impact of books beyond academia. As a unique altmetric data source, Goodreads can allow scholarly authors from the social sciences and humanities to measure the wider impact of their books.

Websites have their own features in aspect preference (e.g. the relative importance platforms place on product aspects in product evaluation). The purpose of this paper is to capture characteristics of different book reviews on aspect preferences by opinion mining techniques.

The authors employ two indicators for identifying aspect preferences, and propose a method for quantifying overall differences of reviews on aspect preferences through three dimensions: aspect awareness, aspect satisfaction and comprehensive value.

The results show that book reviews on e-commerce websites contain information about external aspects of a book (e.g. hardcover), while those on social network websites pay more attention to content-related aspects of the book (e.g. stories). These results indicate that aspect preferences of reviews vary from platforms and make it hard to evaluate book comprehensively based on single-source data. Online book reviews from a wide range of sources can assess book impact from multiple perspectives and dimensions.

In order to illustrate the value of the authors’ method, the authors show book impact assessment based on multi-source data as an application of these difference analyses. Furthermore, the authors present an example of a book promotion to provide customized marketing services for different user clusters.

This study investigates the influence of different data sources on book evaluation from the content of book reviews. The authors also showcase potential applications of these analyses in book impact assessment.

This paper aims to investigate the quality of access to translated fiction published between 2007 and 2011 in six large Canadian public libraries, answering the question about what public libraries can do to help acquaint their readers with international translated fiction.

The article uses the method of bibliographic data analysis based on 2,100 catalog records.

As the results demonstrate, enhanced bibliographic catalog records deliver a wealth of information about translated fiction titles and facilitate meaningful subject access to their contents. At the same time, promotional activities related to translated fiction have room for improvement.

Despite the fact that the study focuses on public libraries, its findings will be of interest not only to public but also academic librarians, any librarian tasked with the selection and acquisition of translated fiction, reference and readers’ advisory librarians in any type of library, Library and Information Science students and anyone interested in access to translated fiction.

While many recent studies have turned their attention to enhanced catalog records and their role in access, discovery and collection promotion, there are no studies dealing with translated fiction specifically. The article also contributes to seeing an in-depth understanding of bibliographic records and cataloging as part and parcel of reference librarians’ knowledge and skill set, which improves retrieval practices and access provision.

This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.

The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.

Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.

The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.

Cool has been studied mostly in consumer samples drawn from Western countries. This study was inspired by paucity of literature on “cool” in an Indian context. There is certainty that “cool” adds value and bestows desirability but there is uncertainty about what “cool” means. Since “cool” is a cultural phenomenon, the purpose of this paper is to explore its meaning in the Indian context.

The data were obtained on an open-ended questionnaire followed by depth probes on a sample of young consumers. The obtained scripts were coded and classified into semantic categories based on the grounded theory.

The study found that cool is indicated by seven facets, including being oneself, living life to the fullest, sense of humor and socially networked, and calm disposition. Unlike Western notions, in India, cool is not being deviant and hedonistic. The cultural and religious imprints are palpable in what is construed as cool in India.

Transplanting the Western notions of cool for brand building is likely to be a risky proposition. It may not resonate with the inner cords of the Indian youth. The implication of this study is that it reveals possible ways in which cool can be incorporated in brand identity.

Cool is valued because it bestows distinction in subtle ways. Brands can gain traction among consumers by incorporating cool symbolism in their identity.

This study expands the understanding of cool in the context of an emerging market. This is one of the first studies to have probed the concept of “cool” in India.