Body text

Body text: Typography and the corporeality of literature In one of his fragments, Georg Christoph Lichtenberg explains that German books printed with roman type, instead of the then default gothic type, always give him a feeling that he needs to translate them – evidence, he says, of “the degree to which our concepts are dependent on these signs”. The article elaborates on this thought. It explores the relation between literature, text (abstract and material), and typography, and argues – by means of bibliographical theory, Goethe’s mother, Jean-Luc Nancy, Roman Ingarden, and a diagnostic comparison between hand writing and digital fonts – that the longstanding, idealistic view, within literary criticism and history, of texts’ ‘content’ as independent of books’ and texts’ materiality and form, obstructs scholars’ striving for understand-ing. Text is not only representation; it is also presentation. Text has form, and the form produces meaning.

How marketer-generated content characteristics affect consumer engagement? Empirical evidence from China's WeChat food marketing

Purpose Leveraging marketer-generated content (MGC) can increase firms' success. However, few studies uncover the effects of MGC-related attributes on consumer engagement in the context of food marketing. This paper aims to explore the influence of MGC characteristics (valence, content types, vividness and interactivity) on consumer engagement.Design/methodology/approachThis study uses WeChat official account data of seven food companies from China and conducts negative binomial regression models.FindingsThe findings indicate that different MGC-related characteristics have separate impacts on consumer WeChat engagement. Title valence, transactional title content and title with punctuation vividness negatively affect consumers' consuming engagement. Knowledgeable or entertaining title content and title with interactivity both positively affect consumers' consuming engagement. Moreover, transactional body text content negatively influences consumers' contributing engagement, whereas entertaining body text content shows positive effects. Vivid and interactive MGC body text attributes enhance consumers' contributing engagement behavior.Originality/value This study contributes to social media research in food marketplaces and sheds light on the effect of different WeChat MGC characteristics on separate consumer engagement.

Correction to: Improvement of Grey System Model using Particle Swarm Optimization

Following publication of the original article [1], the authors reported an error in the title and body text.

Mining Art History: Bulk Converting Nonstandard PDFs to Text to Determine the Frequency of Citations and Key Terms in Humanities Articles

Text mining in art history scholarship can tell us about the discipline itself, as well as artistic concerns at any given moment. The aim of this study is to develop and test a strategy for text mining from PDFs of journal articles that have nonstandard formatting and/or use notes rather than full bibliographies for references. While articles in the natural and social sciences typically adhere to standard formats, art history journals employ a variety of formatting styles that make bulk capture of citation and other textual data from the articles challenging. This study outlines a method by which researchers can extract data from journals articles, using a sample set from art history. Once extracted, the data from PDFs can be used to compare frequently used terms across samples and determine which scholars are most cited in either bibliographies or the main body text of articles. If the structure and layout of individual journals are carefully considered and the data is properly cleaned, a clear picture of the disciplinary influences and dependencies of the scholarship through citations and key terms can be obtained.

Multi-Language Spam/Phishing Classification by Email Body Text: Toward Automated Security Incident Investigation

Spamming and phishing are two types of emailing that are annoying and unwanted, differing by the potential threat and impact to the user. Automated classification of these categories can increase the users’ awareness as well as to be used for incident investigation prioritization or automated fact gathering. However, currently there are no scientific papers focusing on email classification concerning these two categories of spam and phishing emails. Therefore this paper presents a solution, based on email message body text automated classification into spam and phishing emails. We apply the proposed solution for email classification, written in three languages: English, Russian, and Lithuanian. As most public email datasets almost exclusively collect English emails, we investigate the suitability of automated dataset translation to adapt it to email classification, written in other languages. Experiments on public dataset usage limitations for a specific organization are executed in this paper to evaluate the need of dataset updates for more accurate classification results.

Correction: Barnat-Hunek, D., et al. Durability of Hydrophobic/Icephobic Coatings in Protection Lightweight Concrete with Waste Aggregate. Materials 2021, 14, 101

The authors wish to revise in the main body text of 2 [...]