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This research investigates the impact of learners' non-substantive responses in online course forums, referred to as online listening responses, on e-learning performance. A common type of response in online course forums, online listening responses consist of brief, non-substantive replies/comments (e.g. “agree,” “I see,” “thank you,” “me too”) and non-textual inputs (e.g. post-voting, emoticons) in online discussions. Extant literature on online forum participation focuses on learners' active participation with substantive inputs and overlooks online listening responses. This research, by contrast, stresses the value of online listening responses in e-learning and their heterogeneous effects across learner characteristics. It calls for recognition and encouragement from online instructors and online forum designers to support this activity.

The large-scale proprietary dataset comes from a leading MOOC (massive open online courses) platform in China. The dataset includes 68,126 records of learners in five MOOCs during 2014–2018. An ordinary least squares model is used to analyze the data and test the hypotheses.

Online listening responses in course forums, along with learners' substantive inputs, positively influence learner performance in online courses. The effects are heterogeneous across learner characteristics, being more prominent for early course registrants, learners with full-time jobs and learners with more e-learning experience, but weaker for female learners.

This research distinguishes learners' brief, non-substantive responses (online listening responses) and substantive inputs (online speaking) as two types of active participation in online forums and provides empirical evidence for the importance of online listening responses in e-learning. It contributes to online forum research by advancing the active-passive dichotomy of online forum participation to a nuanced classification of learner behaviors. It also adds to e-learning research by generating insights into the positive and heterogeneous value of learners' online listening responses to e-learning outcomes. Finally, it enriches online listening research by introducing and examining online listening responses, thereby providing a new avenue to probe online discussions and e-learning performance.

Women's violence is periodically raised as a cause for concern both in the media as well as in discussions among the general public in other platforms, such as online forums. These concerns are linked with anti-feminist efforts to discredit the benefits of feminisms and to counter feminist knowledge on gendered patterns in violence. In this chapter, I discuss the ways these concerns and the associated discrediting of feminism have been manifested in various contexts, including academic research on intimate partner violence. My specific focus is on online forums, where women's use of violence is frequently highlighted for the purpose of creating an image of reversed gender discrimination experienced by men. I illustrate how such meaning-making is employed in online discussions derived from various online discussion forums in Finland. The empirical example is focussed on identifying discursive methods frequently employed in the online contexts and specifically illustrates how those methods are employed for the rhetorical effect of othering feminists, highlighting the severity of women's violence as a social problem and portraying men instead of women as victims of inequality. I conclude with a discussion on connections between this meaning-making and broader patterns in anti-feminist mobilisations of the issue of women's violence.

Chinese internet literature (CIL) platforms afford freedom for creative expression and opportunities for direct interactions between writers and fans and among fans. Enabled by these platforms' technological and commercial arrangement, a new form of literary production and consumption has emerged, the most significant of which is the role of fans participation. A social network analysis of the interaction patterns in online fan communities was conducted to investigate fan communication activities at scale. Of particular interest is how the socio-technical system of the site influences its network topology.

Online forums for 10 popular fiction titles in Qidian, the leading CIL platform, were analyzed. Social networks were constructed based on a post–reply–reply threaded discussion structure. Various aspects of fan interactions were analyzed, including number of replies per post, post length and emerging network patterns.

Similarities in network topology shared by CIL fan forums and other online communities, such as small-world and scale properties, were discovered; however, distinct network dynamics were also identified. Consistent with previous findings, writers and moderators, along with a few highly ranked fans, occupied the central positions in the network. This was due to their social roles and the nature of their posts rather than, as the conventional explanation goes, preferential attachment.

The findings demonstrate how community-specific circumstances and norms influence interaction patterns and the resultant network structure. It was revealed that in the CIL sites, the users adopted the technologies in unexpected ways. And the resulting network topology can be attributed to the interplay between the sites' official arrangement and users' adaptive tactics.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2021-0596.

Online, distance, and eLearning (ODeL) continue to gain recognition as a mandatory component of delivery of education in institutions of higher learning (IHL) around the world following the outbreak of coronavirus disease (COVID-19). This paradigm shift is informed by the need to ensure uninterrupted, valuable, and safe learning experiences for learners during the pandemic. However, governments ordered the closure of schools and colleges following the declaration of COVID-19 as a world pandemic by the World Health Organization (WHO). A report by United Nations Educational, Scientific and Cultural Organization revealed that there was a significant loss of schooling time following the closure of educational facilities which affected over 1.5 billion learners in 194 nations globally. This study explored the use of online approaches to intensify online learning efficacy in IHL. Data collection was conducted using qualitative methods and data analysis done using themes and sub-themes. Findings from this study indicate that students’ engagements on discussion forums are consistent with collaborative learning. Results further support the view that regular, prompt, and meaningful feedback is critical in promoting constructive learning and reflection among students. Based on the findings of this study, practical implications are discussed for stakeholders interested in establishing and strengthening effective delivery of online learning content to enhance students’ learning experiences.

The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the highest vector embedding. Combining these models is used to optimize the model with increasing accuracy.

The development of the model in the study is divided into seven stages: (1) data collection, (2) pre-processing data, (3) selected pre-trained SentenceTransformers model, (4) semantic similarity (sentence pair), (5) keyword similarity, (6) calculate final score and (7) evaluating model.

The multilingual paraphrase-multilingual-MiniLM-L12-v2 and distilbert-base-multilingual-cased-v1 models got the highest scores from comparisons of 11 pre-trained multilingual models of SentenceTransformers with Indonesian data (Dhini and Girsang, 2023). Both multilingual models were adopted in this study. A combination of two parameters is obtained by comparing the response of the keyword extraction responses with the rubric keywords. Based on the experimental results, proposing a combination can increase the evaluation results by 0.2.

This study uses discussion forum data from the general biology course in online learning at the open university for the 2020.2 and 2021.2 semesters. Forum discussion ratings are still manual. In this survey, the authors created a model that automatically calculates the value of discussion forums, which are essays based on the lecturer's answers moreover rubrics.

With gaining popularity, online communities are increasing. It is leading to the data and information overflow. So, there are some challenges like cyber frauds, cyberbullying, etc. while engaging with online communities. Not only this, anonymity of the participants, stress and racism are also big challenges in online communities' interaction. Online harassers' attack tactics have changed over time. In addition, there are challenges like quality of discussion, inequality in participation of the users, etc. may scale online communities towards incitement and activism. Therefore, this study will try to analyse these challenges for overall benefit of the society.

The underlying fuzzy set theory is employed to handle the fuzziness of users' perceptions since the attributes are expressed in linguistic preferences. Through exhaustive literature review, the authors have identified 15 challenges. These challenges are further categorised as cause and effect by using DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach.

Lack of strategic planning and uninspired discussions between users has emerged as a major challenge in cause category. This study further demonstrates how individual challenge can be managed and developed to navigate the online communities to maintain a healthy environment in society.

Results are based on limited dataset. Therefore, findings cannot be generalised for all online communities.

The research findings offer a suitable direction to policymakers to formulate and design policies, laws and regulations to increase user engagement in the online community. The study is beneficial to firms and researchers in understanding the factors influencing effective management of online communities.

The purpose of this paper is to develop a greater understanding of how a virtual learning environment (VLE) discussion forum can be used as a learning community to enhance reflective practice in work-based learning (WBL).

This study adopted a qualitative interpretive approach through the use of VLE [Blackboard (BB)] discussion forums followed by a focus group. Thematic and content analysis was conducted to identify patterns and themes.

The findings suggest that whilst a VLE can help create a community of practice through discussion forums, individual reflective practice, as opposed to group reflection, was found to be the most common in the communication discourse, with reflection on experience as the main category.

Original views of students have been gathered and can be used to inform future practice.

The findings can be used to better understand and enhance reflective practice of students on WBL placements.

The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners’ online learning behaviors, and comparing three algorithms – multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).

Through literature review and analysis of data correlation in the original database, a framework of online learning behavior indicators containing 26 behaviors was constructed. The degree of correlation with the final learning performance was analyzed based on learners’ system interaction behavior, resource interaction behavior, social interaction behavior and independent learning behavior. A total of 12 behaviors highly correlated to learning performance were extracted as major indicators, and the MLR method, MLP method and CART method were used as typical algorithms to evaluate learners’ MOOC learning performance.

The behavioral indicator framework constructed in this study can effectively analyze learners’ learning, and the evaluation model constructed using the MLP method (89.91%) and CART method (90.29%) can better achieve the prediction of MOOC learners’ learning performance than using MLR method (83.64%).

This study explores the patterns and characteristics among different learning behaviors and constructs an effective prediction model for MOOC learners’ learning performance, which can help teachers understand learners’ learning status, locate learners with learning difficulties promptly and provide targeted instructional interventions at the right time to improve teaching quality.

This article aims to elaborate the context-sensitive nature of credibility assessment by examining how such judgments are made in online discussion in times of uncertainty caused by Finland's intent to join the North Atlantic Treaty Organization (NATO) in spring 2022.

The empirical findings draw on the qualitative content analysis of 3,324 posts submitted to a Finnish online discussion in February–March 2022. It was examined how the participants of online discussion assess the credibility of information sources referred to in debates on the NATO membership. It is assumed that the believability of the author of information is indicative of his or her expert power, for example based on the credentials of a scholar, while the credibility of information content, for example the provision of factual evidence is indicative of the source's informational power.

Political decision-makers, particularly the President of Finland were assessed as most credible information sources, due to their access to confidential knowledge and long-time experience in politics. The credibility assessments differed more strongly while judging the believability of researchers. On the one hand, their expertise was praised; on the other hand, doubts were presented about their partiality. Fellow participants of online discussion were assessed most negatively because information sources of these types are associated with low expert and informational power.

As the study concentrated on credibility assessments made in a Finnish online discussion group, the findings cannot be extended to concern the credibility judgments occurring information in other contexts.

The study is among the first to characterize the role of expert and informational power in credibility assessment in times of uncertainty.

Information on the impact of flooding is fundamental to mitigating flood risk in residential property. This paper aims to provide insight into the seller disclosure of flood risk and buyer behaviour in the absence of mandated seller disclosure.

This paper adopts a case study approach to critically evaluate the matrix of flood information available for buyers purchasing residential property in Brisbane, Queensland. This paper uses big data analytic techniques to extract and analyse internet data from online seller agents and buyer platforms to gain an understanding of buyer awareness and consideration of flood risk in the residential property market.

Analysis of property marketing data demonstrates that seller agents voluntarily disclose flood impact only in periods where a flooding event is anticipated and is limited to asserting a property is free of flood risk. Analysis of buyer commentary demonstrates that buyers are either unaware of flood information or are discounting the risk of flood in favour of other property and locational attributes when selecting residential property.

This research suggests that improved and accessible government-provided flood mapping tools are not enhancing buyers’ understanding and awareness of flood risk. Accordingly, it is recommended that mandatory disclosure be introduced in Queensland so that buyers are more able to manage risk and investment decisions before the purchase of residential property.

This paper contributes to existing literature on raising community awareness and understanding of natural disaster risks and makes a further contribution in identifying mandatory disclosure as a mechanism to highlight the risk of flooding and inform residential property purchasers.