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The purpose of this paper is to analyze the readability and level of word complexity of search engine results pages (SERPs) snippets and associated web pages between Google and Bing.

The authors employed the Readability Test Tool to analyze the readability and word complexity of 3,000 SERPs snippets and 3,000 associated pages in Google and Bing retrieved on 150 search queries issued by middle school children.

A significant difference was found in the readability of SERPs snippets and associated web pages between Google and Bing. A significant difference was also observed in the number of complex words in snippets between the two engines but not in associated web pages. At the engine level, the readability of Google and Bing snippets was significantly higher than associated web pages. The readability of Google SERPs snippets was at a much higher level than those of Bing. The readability of snippets in both engines mismatched with the reading comprehension of children in grades 6–8.

The data corpus may be small. Analysis relied on quantitative measures.

Practitioners and other mediators should mitigate the readability issue in SERPs snippets. Researchers should consider text readability and word complexity simultaneously with other factors to obtain the nuanced understanding of young users’ web information behaviors. Additional theoretical and methodological implications are discussed.

This study measured the readability and the level of word complexity embedded in SERPs snippets and compared them to respective web pages in Google and Bing. Findings provide further evidence of the readability issue of SERPs snippets and the need to solve this issue through system design improvements.

The purpose of this paper is to explore to which extent the quality of social media short text without extensions can be investigated and what are the predictors, if any, of such short text that lead to trust its content.

The paper applies a trust model to classify data collections based on metadata into four classes: Very Trusted, Trusted, Untrusted and Very Untrusted. These data are collected from the online communities, Genius and Stack Overflow. In order to evaluate short texts in terms of its trust levels, the authors have conducted two investigations: (1) A natural language processing (NLP) approach to extract relevant features (i.e. Part-of-Speech and various readability indexes). The authors report relatively good performance of the NLP study. (2) A machine learning technique in more precise, a random forest (RF) classifierusing bag-of-words model (BoW).

The investigation of the RF classifier using BoW shows promising intermediate results (on average 62% accuracy of both online communities) in short-text quality identification that leads to trust.

As social media becomes an increasingly new and attractive source of information, which is mostly provided in the form of short texts, businesses (e.g. in search engines for smart data) can filter content without having to apply complex approaches and continue to deal with information that is considered more trustworthy.

Short-text classifications with regard to a criterion (e.g. quality, readability) are usually extended by an external source or its metadata. This enhancement either changes the original text if it is an additional text from an external source, or it requires text metadata that is not always available. To this end, the originality of this study faces the challenge of investigating the quality of short text (i.e. social media text) without having to extend or modify it using external sources. This modification alters the text and distorts the results of the investigation.

This paper aims to examine and critique the accounting literature's dominant readability formula, the Flesch formula. Furthermore, the paper sets out to propose refinement and augmentation to the formula with a view to expanding its applicability and relevance to researchers' attempts at better understanding and critiquing the effectiveness of accounting communications. This aim extends to setting a more robust foundation for informing policymakers' and practitioners' interest in implementing more effective communications with their target stakeholders.

The paper offers an historically informed methodological critique of the current articulation and application of the Flesch formula, both generally and in accounting research. This critique forms the basis for developing proposed revisions and supplementary measures to augment Flesch's coverage. These are presented with sample empirics.

Illustrative examples suggest that it is feasible and desirable to apply a revised formula that reduces Flesch's misplaced emphasis on word length by respecifying its sentence length variable, a probable cause of low readability. A reader attribute score further enhances the formula by integrating the considerable impact of readers' attributes on readability and accounting communication effectiveness. Supplementary measures, comprising non‐narrative communications dimensions, are introduced as a foundation for further research.

The paper provides not only critique but also refinement and augmentation of the much used Flesch readability formula for accounting communications research. It offers a first stage approach to encompassing potentially important communication elements such as readers' attributes, tables, graphs and headings, to date critiqued as potentially important but left unattended by accounting researchers. This offers the prospect of extending Flesch's application to contemporary accounting communications issues and questions.

The degree to which a text is considered readable depends on the capability of the reader. This assumption puts different information retrieval systems at the risk of retrieving unreadable or hard-to-be-read yet relevant documents for their users. This paper aims to examine the potential use of concept-based readability measures along with classic measures for re-ranking search results in information retrieval systems, specifically in the Persian language.

Flesch–Dayani as a classic readability measure along with document scope (DS) and document cohesion (DC) as domain-specific measures have been applied for scoring the retrieved documents from Google (181 documents) and the RICeST database (215 documents) in the field of computer science and information technology (IT). The re-ranked result has been compared with the ranking of potential users regarding their readability.

The results show that there is a difference among subcategories of the computer science and IT field according to their readability and understandability. This study also shows that it is possible to develop a hybrid score based on DS and DC measures and, among all four applied scores in re-ranking the documents, the re-ranked list of documents based on the DSDC score shows correlation with re-ranking of the participants in both groups.

The findings of this study would foster a new option in re-ranking search results based on their difficulty for experts and non-experts in different fields.

The findings and the two-mode re-ranking model proposed in this paper along with its primary focus on domain-specific readability in the Persian language would help Web search engines and online databases in further refining the search results in pursuit of retrieving useful texts for users with differing expertise.

Existing studies on the relationship between task description and task performance are insufficient, with many studies considering description length rather than content to measure quality or only evaluating a single aspect of task performance. To address this gap, this study analyzes the linguistic styles of task descriptions from 2,545 tasks on the Taskcn.com crowdsourcing platform.

An empirical analysis was completed for task description language styles and task performance. The paper used text mining tool Simplified Chinese Linguistic Inquiry and Word Count to extract eight linguistic styles, namely readability, self-distancing, cognitive complexity, causality, tentative language, humanizing personal details, normative information and language intensity. And it tests the relationship between the eight language styles and task performance.

The study found that more cognitive complexity markers, tentative language, humanized details and normative information increase the quantity of submissions for a task. In addition, more humanized details and normative information in a task description improves the quality of task. Conversely, the inclusion of more causal relationships in a task description reduces the quantity of submissions. Poorer readability of the task description, less self-estrangement and higher language intensity reduces the quality of the task.

This study first reveals the importance of the linguistic styles used in task descriptions and provides a reference for how to attract more task solvers and achieve higher quality task performance by improving task descriptions. The research also enriches existing knowledge on the impact of linguistic styles and the applications of text mining.

Readability applications are the software products designed to make online text more readable. Using information foraging theory as a framework, the purpose of this paper is to study the extent, if at all, using a readability application improves skimming comprehension in a low-clutter online environment. It also seeks to identify the perceived benefits or effects of using a readability application for skimming comprehension.

Ten participants skimmed two articles each, one in a low-clutter online document presentation environment, the other using an online readability application, as a timed, information foraging exercise. After reading each article, respondents answered true/false comprehension questions and follow up questions.

There was little difference in the comprehension of respondents after skimming in the two online documentation presentation environments. The readability environment was the preferred environment.

This study suggests that since participants claimed to prefer the text presentation of the readability application interface, interface designers may wish to create library interfaces for information seeking that follow the readability application format. Because some of the participants found themselves reading rather than skimming when using the readability application, readability for tasks other than skimming may be enhanced.

This is a practical study investigating an existing online readability application and its effects on an existing online reading environment as they pertain to information seeking behavior in general and to information foraging in particular.

In this study, various acts including regulations of public financial management, fiscal responsibility, and state budget in the selected six countries were subjected to different readability tests, and an international comparison was made. The fiscal responsibility act of six countries – Turkey, the UK, India, Australia, Canada, and Pakistan – were included in the study and analyzed. Each country was analyzed under its official language. Since English is an official language of all of the countries except for Turkey, the authors have evaluated the fiscal responsibility acts of these countries using the following readability tests: Flesch Reading Ease, Flesch-Kincaid, Gunning-Fog, and Dale-Chall. Additionally, Public Financial Management and Control Law No. 5018 approved in Turkey was analyzed by the Ateşman Readability Test which was uniquely designed for Turkish grammar rules. The acts discussed in the study were analyzed not only as a whole but also in parts and subsections. According to the results of the study, the levels of readability of the existing laws in most of the selected countries are very difficult to understand for a university graduate. However, when the readability level of the British Budget Responsibility and National Audit Act tested as parts and subsections and a whole, it was rated at a level a university student could understand. This study analyses the readability and intelligibility of acts related to fiscal responsibility and the state budget in six selected countries, adopting Anglo-Saxon public administration model and making an inter-country evaluation. Since it is important that citizens have enough information about legislation for a citizen-oriented understanding, a legislation system that is understood by the larger part of the society is essential.

This study aims to draw the attention of business process management (BPM) research and practice to the textual data generated in the processes and the potential of meaningful insights extraction. The authors apply standard natural language processing (NLP) approaches to gain valuable knowledge in the form of business process (BP) complexity concept suggested in the study. It is built on the objective, subjective and meta-knowledge extracted from the BP textual data and encompassing semantics, syntax and stylistics. As a result, the authors aim to create awareness about cognitive, attention and reading efforts forming the textual data-based BP complexity. The concept serves as a basis for the development of various decision-support solutions for BP workers.

The starting point is an investigation of the complexity concept in the BPM literature to develop an understanding of the related complexity research and to put the textual data-based BP complexity in its context. Afterward, utilizing the linguistic foundations and the theory of situation awareness (SA), the concept is empirically developed and evaluated in a real-world application case using qualitative interview-based and quantitative data-based methods.

In the practical, real-world application, the authors confirmed that BP textual data could be used to predict BP complexity from the semantic, syntactic and stylistic viewpoints. The authors were able to prove the value of this knowledge about the BP complexity formed based on the (1) professional contextual experience of the BP worker enriched by the awareness of cognitive efforts required for BP execution (objective knowledge), (2) business emotions enriched by attention efforts (subjective knowledge) and (3) quality of the text, i.e. professionalism, expertise and stress level of the text author, enriched by reading efforts (meta-knowledge). In particular, the BP complexity concept has been applied to an industrial example of Information Technology Infrastructure Library (ITIL) change management (CHM) Information Technology (IT) ticket processing. The authors used IT ticket texts from two samples of 28,157 and 4,625 tickets as the basis for the analysis. The authors evaluated the concept with the help of manually labeled tickets and a rule-based approach using historical ticket execution data. Having a recommendation character, the results showed to be useful in creating awareness regarding cognitive, attention and reading efforts for ITIL CHM BP workers coordinating the IT ticket processing.

While aiming to draw attention to those valuable insights inherent in BP textual data, the authors propose an unconventional approach to BP complexity definition through the lens of textual data. Hereby, the authors address the challenges specified by BPM researchers, i.e. focus on semantics in the development of vocabularies and organization- and sector-specific adaptation of standard NLP techniques.

The citation counts are an important indicator of scholarly impact. The purpose of this paper is to explore the correlation between citations of scientific articles and writing styles of abstracts in papers and capture the characteristics of highly cited papers' abstracts.

This research selected 10,000 highly cited papers and 10,000 zero-cited papers from the WOS (2008-2017) database. The Coh-Metrix 3.0 textual cohesion analysis tool was used to quantify the 108 language features of highly cited and zero-cited paper abstracts. The differences of the indicators with significant differences were analyzed from four aspects: vocabulary, sentence, syntax and readability.

The abstracts of highly cited papers contain more complex and professional words, more adjectives, adverbs, conjunctions and personal pronouns, but fewer nouns and verbs. The sentences in the abstracts of highly cited papers are more complex and the sentence length is relatively longer. The syntactic structure in abstracts of highly cited papers is relatively more complex and syntactic similarities between sentences are fewer. Highly cited papers' abstracts are less readable than zero-cited papers' abstracts.

This study analyses the differences between the abstracts of highly cited and those of zero-cited papers, reveals the common external and deep semantic features of highly cited papers in abstract writing styles, provide suggestions for researchers on abstract writing. These findings can help increase the scientific impact of articles and improve the review efficiency as well as the researchers' abstract writing skills.

The obfuscation hypothesis suggests that under‐performing firms will tend to obscure the meaning of their corporate narratives by deliberately adopting a textual complexity, most readily apparent through poor readability and the use of unnecessarily difficult language. This paper seeks to add to the literature in the area by comparing the textual complexity of corporate narratives, notably the chairman's statement, of main board and second board companies on the Bursa Malaysia (formerly known as the Kuala Lumpur Stock Exchange), with their financial performance, and also to examine the impact of company size, board membership and degree of statutory regulation on the readability of corporate narratives.

Following the existing literature this paper uses readability as a proxy for textual complexity, in addition to more direct measures, and seeks to examine relationships between textual complexity and various measures of financial performance.

The findings suggest that there are significant relationships between corporate language and financial performance, but that these are not consistent with the obfuscation hypothesis.

The findings are consistent with the suggestion that increased regulation and statutory monitoring of disclosures are associated with improved readability of narrative. They do not provide support for the obfuscation hypothesis.