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Software developers extensively use stack overflow (SO) for knowledge sharing on software development. Thus, software engineering researchers have started mining the structured/unstructured data present in certain software repositories including the Q&A software developer community SO, with the aim to improve software development. The purpose of this paper is show that how academics/practitioners can get benefit from the valuable user-generated content shared on various online social networks, specifically from Q&A community SO for software development.

A comprehensive literature review was conducted and 166 research papers on SO were categorized about software development from the inception of SO till June 2016.

Most of the studies revolve around a limited number of software development tasks; approximately 70 percent of the papers used millions of posts data, applied basic machine learning methods, and conducted investigations semi-automatically and quantitative studies. Thus, future research should focus on the overcoming existing identified challenges and gaps.

The work on SO is classified into two main categories; “SO design and usage” and “SO content applications.” These categories not only give insights to Q&A forum providers about the shortcomings in design and usage of such forums but also provide ways to overcome them in future. It also enables software developers to exploit such forums for the identified under-utilized tasks of software development.

The study is the first of its kind to explore the work on SO about software development and makes an original contribution by presenting a comprehensive review, design/usage shortcomings of Q&A sites, and future research challenges.

In the Web 2.0 era, more and more digital immigrants actively participate in blogging, video sharing, online rating, and micro blogging, etc. However, some may be more skilled in producing and generating online content while others still meet some barriers in doing so. Thus, it is interesting to investigate the online generative capability of digital immigrants in Web 2.0 context. This paper seeks to address this issue.

The authors selected Shanghai as their target province in this study for its large scale of internet users. An in-depth semi-structured interview was used as their research method. They selected several community clubs as the interview settings. In addition, age was adopted as a threshold to define the Chinese digital immigrants for its convenience in sampling.

Chinese digital immigrants are playing an important role in content generating, and have a great potential in the future contribution, and a number of digital immigrants regard the content generating as a pretty easy work while some others felt difficulties, even frustrated and exhausted when generating content. About the content type, digital immigrants prefer to generate that content with low granularity. About the motivation, the intrinsic motivation and the extrinsic motivation with an internalized focus play a dominant role. About the generating mode, digital immigrants prefer to generate content individually or collectively.

This paper develops the concept of online generative capability by adapting the notion of generativity from other disciplines to the characteristics of Web 2.0. Then an integrated conceptual framework is built and evaluated. Practically, the paper puts forward some implications for the designers, managers, and information service staff from different perspectives to facilitate the digital immigrant's online generative capability.

This study aimed to examine the mental health information entities and associations between the biomedical, psychological and social domains of bipolar disorder (BD) by analyzing social media data and scientific literature.

Reddit posts and full-text papers from PubMed Central (PMC) were collected. The text analysis was used to create a psychological dictionary. The text mining tools were applied to extract BD entities and their relationships in the datasets using a dictionary- and rule-based approach. Lastly, social network analysis and visualization were employed to view the associations.

Mental health information on the drug side effects entity was detected frequently in both datasets. In the affective category, the most frequent entities were “depressed” and “severe” in the social media and PMC data, respectively. The social and personal concerns entities that related to friends, family, self-attitude and economy were found repeatedly in the Reddit data. The relationships between the biomedical and psychological processes, “afraid” and “Lithium” and “schizophrenia” and “suicidal,” were identified often in the social media and PMC data, respectively.

Mental health information has been increasingly sought-after, and BD is a mental illness with complicated factors in the clinical picture. This paper has made an original contribution to comprehending the biological, psychological and social factors of BD. Importantly, these results have highlighted the benefit of mental health informatics that can be analyzed in the laboratory and social media domains.

Social question and answer (SQA) site is one of the factors that boosted up and popularized the vision of social web. It enables community members to post highly valued answers to globally asked questions and information seekers to grab intellectual information in a contextual, concise, and meaningful format at the cost of investing a few minutes. The purpose of this paper is to present a common architecture, history, and a comprehensive review of such sites.

A critical and analytical investigation of the state-of-the-art SQA sites and relevant literature has been carried out with the intention to explore the noticeable features of such sites.

By studying relevant literature, and analysing a number of existing systems, a number of research challenges are identified and a generic architecture of SQA sites is contributed.

The review contributes a comprehensive knowledge about SQA systems and aims to be helpful to new researchers who want to get a broad picture of SQA systems on a single platform. The domain is in its infancy and requires tremendous efforts from the research community to explore its salient aspects with respect to the human world.

The study inspects SQA sites on a large scale and makes an original contribution by presenting a comprehensive review, future research challenges, and a generic architecture of SQA sites.

The purpose of this paper is to investigate longitudinal features of an established social question-answering (Q&A) site to study how question-answer resources and other community features change over time.

Statistical analysis and visualisation was performed on the full data dump from the Stack Overflow social Q&A site for programmers.

The timing of answers is as strong a predictor of acceptance – a proxy for user satisfaction – as the structural features of provided answers sometimes associated with quality. While many questions and answer exchanges are short-lived, there is a small yet interesting subset of questions where new answers receive community approval and which may end up being ranked more highly than early answers.

As a large-scale data oriented research study, this work says little about user motivations to find and contribute new knowledge to old questions or about the impact of the resource on the consumer. This will require complementary studies using qualitative and evaluative methods.

While content contribution to social question-asking is largely undertaken within a very short time frame, content consumption is usually over far longer periods. Methods and incentives by which content can be updated and maintained need to be considered. This work should be of interest to knowledge exchange community designers and managers.

Few studies have looked at temporal patterns in social Q&A and how time and the moderation and voting systems employed may shape resource quality.

Academic social (question and answer) Q&A sites are now utilised by millions of scholars and researchers for seeking and sharing discipline-specific information. However, little is known about the factors that can affect their votes on the quality of an answer, nor how the discipline might influence these factors. The paper aims to discuss this issue.

Using 1,021 answers collected over three disciplines (library and information services, history of art, and astrophysics) in ResearchGate, statistical analysis is performed to identify the characteristics of high-quality academic answers, and comparisons were made across the three disciplines. In particular, two major categories of characteristics of the answer provider and answer content were extracted and examined.

The results reveal that high-quality answers on academic social Q&A sites tend to possess two characteristics: first, they are provided by scholars with higher academic reputations (e.g. more followers, etc.); and second, they provide objective information (e.g. longer answer with fewer subjective opinions). However, the impact of these factors varies across disciplines, e.g., objectivity is more favourable in physics than in other disciplines.

The study is envisioned to help academic Q&A sites to select and recommend high-quality answers across different disciplines, especially in a cold-start scenario where the answer has not received enough judgements from peers.

This paper aims to explore question and answer (Q&A) participation and behavioral patterns on academic social networking sites (ASNSs) from the perspective of multiple subjects such as academic, corporate and government institutions.

Focused on the Q&A service of ASNSs, this study chooses ResearchGate (RG) as the target ASNS and collects a large-scale data set from it, involving a sample of users and a Q&A sample about academic, corporate and government institutions. First, it studies the law of Q&A participation and the distribution of the type of user according to the sample of users. Second, it compares question-asking behavior and question-answering behavior stimulated by questions among the three types of institutions based on the Q&A sample. Finally, it discusses the Q&A participation and behavioral patterns of the three types of institutions in academic Q&A exchanges with full consideration of institutional attributes, and provides some suggestions for institutions and ASNSs.

The results show that these three types of institutions generally have a low level of participation in the Q&A service of RG, and the numbers of questions and answers proposed by institutional users conform to the power-law distribution. There are differences in Q&A participation and Q&A behavioral patterns among academic, corporate and government institutions. Government and academic institutions have more users participating in the Q&A service and their users are more willing to ask questions, while corporate institutions have fewer users who participate in the Q&A service and their users are inclined to provide answers. Questions from corporate institutions attract much more attention than those from the other two types of institutions.

This study reveals and compares the Q&A participation and the behavioral patterns of the three types of institutions in academic Q&A, thus deepening the understanding of the attributes of institutions in the academic information exchange context. In practice, the results can help guide different institutions to use the Q&A service of ASNSs more effectively and help ASNSs to better optimize their Q&A service.

Social question and answer (social Q&A) sites have become a popular tool for obtaining music information. The purpose of this paper is to investigate what users ask about, what experience the questions convey, and how users specify their questions.

A total of 3,897 music questions from the social Q&A site Yahoo! Answers were categorized according to their question type, user experience, and question specification.

The music questions were diverse with (dis)approval (42 percent), factual (21 percent), and advice (15 percent) questions as the most frequent types. Advice questions were the longest and roughly twice as long as (dis)approval and factual questions. The user experience associated with the questions was most often pragmatic (24 percent) or senso-emotional (12 percent). Pragmatic questions were typically about the user’s own performance of music, while senso-emotional questions were about finding music for listening. Notably, half of the questions did not convey information about the user experience but the absence of such information did not reduce the number of answers. In specifying the questions, the most frequent information was about the music context and the user context.

This study suggests a division of labor between social Q&A sites and search engines for music information retrieval. It should be noted that the study is restricted to one social Q&A site.

Social Q&A sites provide an opportunity for studying what information real users seek about music and what information they specify to retrieve it, thereby elucidating the role of social Q&A in music information seeking.

The purpose of this paper is to focus on active users who are key contributors to online social question-and-answer (Q&A) sites, and examine antecedents of their knowledge-sharing continuance intention, based on expectation-confirmation theory and organizational justice theory.

Sample data were gathered via an online survey from active users of Naver Knowledge-iN, a popular online social Q&A site in South Korea. Partial least squares structural equation modeling was adopted for data analysis. Moreover, a multi-group analysis was conducted to identify the motivators and hygiene factors of the responders’ knowledge-sharing continuance.

Except for perceived self-worth, all the antecedents – perceived playfulness, confirmation, perceived justice with sites, and perceived justice with askers – seemed to have a considerable influence on active users’ satisfaction, and therefore their continuance intention. Among them, perceived playfulness was proven to be a motivator, and perceived justice with sites a hygiene factor.

Despite the limitations of a cross-sectional study, this research successfully illustrated that active users’ continuance intention is influenced by perceived playfulness, and not by perceived self-worth. In addition, perceived justice with social Q&A sites was proven to decrease dissatisfaction (i.e. hygiene factor), while perceived playfulness was proven to increase satisfaction (i.e. motivator).

This study differentiates itself from prior research by focusing specifically on active users of social Q&A sites, since their motivating mechanisms are different from normal users. Additionally, the antecedents of knowledge-sharing continuance were categorized into motivators and hygiene factors. This approach affords detailed guidelines to facilitate active users’ knowledge-sharing continuance and to prevent their defection.

The purpose of this paper is to identify sexual health information needs and the cognitive and affective factors correlated with the best answer chosen by social Q&A users.

The study collected questions and answers regarding sexual health information on a social Q&A site, and analyzed the questions and a paired sample composed of best and non-best answers (n=480).

The main information needs of consumers are human development, sexual behavior, and sexual health. Best answers are more likely to include both cognitive (higher level of readability, risky information, social norms) and affective factors (empathy, positive/negative feelings, and optimistic information) than non-best answers.

The study illuminates the roles of social Q&A as a unique platform to discuss sensitive health topics due to the fact that consumers use such social media sites as critical complementary health information sources.

If health information providers develop information with the factors that the study suggests, not only will it be more adopted by consumers, but it will also ameliorate the quality concerns about online health information.

Previous studies only investigated the most prevalent factors, rather than the most effective ones, which have a greater influence on best answer selection. This study compares the best answers and the non-best answers to overcome the limitations of the previous studies. Above all, the study applied the persuasion concepts to address the cognitive and affective perspectives to the answer evaluations of social Q&A.