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Online knowledge communities have emerged as crucial places for knowledge and risk management in the face of systemic risks. The vitality of online knowledge communities requires users’ active engagement. This research paper aims to explore how text complex level and text analytic level as effective risk knowledge design leverages encourage users’ engagement under different “riskification” levels.

This paper performs linguistic analysis on 210 TED talk transcripts and 38,377 comments from 2002 to 2018. The authors construct the variable of text complex level and conduct ordinary least squares regressions to test the relationships among text complex level, text analytic level and user engagement under different levels of “riskification” in the online knowledge community.

High text complex level decreases engagement, while high text analytic level increases engagement. A high level of “riskification” exaggerates the negative effect of text complex level but diminishes the positive effect of the text analytic level.

This research advances knowledge management by highlighting users’ engagement and responding to shared risk knowledge from a different perspective than knowledge supply. The focus on risk communication in online knowledge communities broadens the scope of knowledge management literature beyond the confines of organizations. To the best of the authors’ knowledge, this research is among the first studies to propose risk knowledge design approaches for communicating systemic risks.

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 number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

Researchers and teachers have noted the power of students reading text sets or multiple texts on the same topic, and numerous articles have been published with examples of and frameworks for text set construction. This study aims to traces the theoretical assumptions of these frameworks and explores their distinct implications and tensions for understanding disciplinary literacy in English language arts (ELA).

The author draws on three frameworks, using a focal article for each: cognitive (Lupo et al., 2018), critical (Lechtenberg, 2018) and disciplinary (Levine et al., 2018), and connect those articles to other research studies in that tradition. Separately, the author describes each of the three text set frameworks’ design principles. Then, across frameworks, the author analyze the disciplinary assumptions around each framework’s centering texts, epistemological goals and trajectories.

The centering text, goals and trajectories of each framework reflect its underlying epistemological lens. All frameworks include a text that serves as its epistemological center and the cognitive and disciplinary frameworks, both rely on progressions of complexity (knowledge/linguistic and literary, respectively). The author traces additional alignments and tensions between the frameworks and offer suggestions for possible hybridities in reading modality and reading volume.

Many articles have been written about models of text set construction, but few have compared the assumptions behind those models. Examining these assumptions may help English teachers and curriculum designers select texts and build curriculum that leverages the strengths of each model and informs researchers’ understanding of disciplinary literacy in ELA.

The current predominant delivery format resulting from digitization is PDF, which is not appropriate for the blind, partially sighted and people who read on mobile devices. To meet the needs of both communities, as well as broader ones, alternative file formats are required. With the findings of the eBooks-On-Demand-Network Opening Publications for European Netizens project research, this study aims to improve access to digitized content for these communities.

In 2022, the authors conducted research on the digitization experiences of 13 EODOPEN partners at their organizations. The authors distributed the same sample of scans in English with different characteristics, and in accordance with Web content accessibility guidelines, the authors created 24 criteria to analyze their digitization workflows, output formats and optical character recognition (OCR) quality.

In this contribution, the authors present the results of a trial implementation among EODOPEN partners regarding their digitization workflows, used delivery file formats and the resulting quality of OCR results, depending on the type of digitization output file format. It was shown that partners using the OCR tool ABBYY FineReader Professional and producing scanning outputs in tagged PDF and PDF/UA formats achieved better results according to set criteria.

The trial implementations were limited to 13 project partners’ organizations only.

This research paper can be a valuable contribution to the field of massive digitization practices, particularly in terms of improving the accessibility of the output delivery file formats.

The purpose of this study was to examine how teachers’ constructions of youth inform their text selections, particularly as they relate to a problematic author.

As part of a larger, national study, the authors use interview data from 18 participants – 9 who still teach and 9 who no longer teach Alexie – to consider how teachers’ constructions of youth play roles in their decisions to teach or avoid complex and controversial authors and topics, specifically the work and life of Sherman Alexie in the #MeToo era.

Findings suggest teachers who constructed youth through asset-based frameworks – as complex and capable – were likely to keep teaching Alexie or have conversations about the #MeToo movement. Teachers who constructed students in deficit ways, as “not ready,” harkened back to Lesko’s (2012) critique, and were more likely to either remove Alexie from the curriculum entirely or engage students in conversations about the text only, leaving Alexie’s life out of the classroom.

Building on Lesko’s work on constructions of adolescence and its intersection with Petrone et al.’s youth lens and Critical Youth Studies (e.g., Petrone and Lewis, 2021), this study describes the ways in which teachers’ views of students served as rationales for their teaching decisions around whether, if or how to include the works and life of Sherman Alexie.

Teacher educators in rural settings where few English learners (ELs) may be enrolled in PK-12 schools are responsible for creating learning experiences that support preservice teachers in building a foundation for teaching culturally and linguistically diverse learners. The goal of the self-study described in this chapter was to investigate a teacher educator’s practice in a largely White, English-speaking rural area in the northeastern US. Learning experiences embedded in the one required course for preparing to teach ELs were grounded in extant research. This chapter highlights one unique experience in which the preservice teachers interacted with international ESL peers on campus to negotiate meaning of a complex text. The preservice teachers reported that this interaction led to analogous understandings for planning and implementing literacy instruction with ELs. These results may be useful to other teacher educators in rural areas who seek principled ways to strengthen preservice teachers’ preparedness for teaching ELs.

A substantial number of students read significantly below grade level, and students with disabilities perform far below their non-disabled peers. Reading achievement data indicate that many students with and at-risk for reading disabilities require more intensive reading interventions. This chapter utilizes the theoretical model of the Simple View of Reading to describe the benefit of early reading instruction, targeting both word reading and word meaning. In addition, evidence is presented supporting the use of word meaning instruction to improve accurate and efficient word reading for students who have failed to respond to explicit decoding instruction.

This study aims to explore the intelligibility of communication with stakeholders as a result of accrual accounting adoption. It focuses on changes in the use of visual forms and the readability of text that occurred immediately after the adoption of accrual accounting in performance reports of Italian public universities.

The authors collect the stakeholder section of performance reports published before and after accrual accounting adoption. Then, the authors use manual and computer-assisted textual analysis. Finally, the authors explore the data using principal component analysis and qualitative comparative analysis.

This study demonstrates that switching from cash to accrual accounting provokes immediate changes in communication patterns. It confirms the significant reduction of readability and increase in visual forms after accruals accounting adoption. The results indicate that smaller universities especially put effort into increasing intelligibility while implementing a more complex accounting system. This study also finds a relation between the change in readability and the change in visual forms that are complementary, with the exception of several very large universities.

The findings underline the possibility of neutralising the adverse effects of accounting reform associated with its complexity and difficulties in understanding by the use of visual forms and attention to the document’s readability.

This paper adds a new dimension to the study of public sector accounting from the external stakeholder perspective. It provides further insight into the link between accrual accounting adoption and readability, together with the use of visual forms by universities.