Dataset Information

Patterns of interest change in stack overflow.

ABSTRACT: Stack Overflow is currently the largest programming related question and answer community, containing multiple programming areas. The change of user's interest is the micro-representation of the intersection of macro-knowledge and has been widely studied in scientific fields, such as literature data sets. However, there is still very little research for the general public, such as the question and answer community. Therefore, we analyze the interest changes of 2,307,720 users in Stack Overflow in this work. Specifically, we classify the tag network in the community, vectorize the topic of questions to quantify the user's interest change patterns. Results show that the change pattern of user interest has the characteristic of a power-law distribution, which is different from the exponential distribution of scientists' interest change, but they are all affected by three features, heterogeneity, recency and proximity. Furthermore, the relationship between users' reputations and interest changes is negatively correlated, suggesting the importance of concentration, i.e., those who focus on specific areas are more likely to gain a higher reputation. In general, our work is a supplement to the public interest changes in science, and it can also help community managers better design recommendation algorithms and promote the healthy development of communities.

SUBMITTER: Fu C

PROVIDER: S-EPMC9259656 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Patterns of interest change in stack overflow.

Fu Chenbo C Yue Xinchen X Shen Bin B Yu Shanqing S Min Yong Y

Scientific reports 20220706 1

Stack Overflow is currently the largest programming related question and answer community, containing multiple programming areas. The change of user's interest is the micro-representation of the intersection of macro-knowledge and has been widely studied in scientific fields, such as literature data sets. However, there is still very little research for the general public, such as the question and answer community. Therefore, we analyze the interest changes of 2,307,720 users in Stack Overflow i ...[more]

PMID: 35794248

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Project description:Increasing biomedical workforce diversity remains a persistent challenge. Recent reports have shown that biomedical sciences (BMS) graduate students become less interested in faculty careers as training progresses; however, it is unclear whether or how the career preferences of women and underrepresented minority (URM) scientists change in manners distinct from their better-represented peers. We report results from a survey of 1500 recent American BMS Ph.D. graduates (including 276 URMs) that examined career preferences over the course of their graduate training experiences. On average, scientists from all social backgrounds showed significantly decreased interest in faculty careers at research universities, and significantly increased interest in non-research careers at Ph.D. completion relative to entry. However, group differences emerged in overall levels of interest (at Ph.D. entry and completion), and the magnitude of change in interest in these careers. Multiple logistic regression showed that when controlling for career pathway interest at Ph.D. entry, first-author publication rate, faculty support, research self-efficacy, and graduate training experiences, differences in career pathway interest between social identity groups persisted. All groups were less likely than men from well-represented (WR) racial/ethnic backgrounds to report high interest in faculty careers at research-intensive universities (URM men: OR 0.60, 95% CI: 0.36-0.98, p = 0.04; WR women: OR: 0.64, 95% CI: 0.47-0.89, p = 0.008; URM women: OR: 0.46, 95% CI: 0.30-0.71, p<0.001), and URM women were more likely than all other groups to report high interest in non-research careers (OR: 1.93, 95% CI: 1.28-2.90, p = 0.002). The persistence of disparities in the career interests of Ph.D. recipients suggests that a supply-side (or "pipeline") framing of biomedical workforce diversity challenges may limit the effectiveness of efforts to attract and retain the best and most diverse workforce. We propose incorporation of an ecological perspective of career development when considering strategies to enhance the biomedical workforce and professoriate through diversity.

Project description:BackgroundConsidering the finite time within a 24-h day, the distribution of time spent on movement behaviours has been found to be associated with health outcomes.ObjectivesThis systematic review and meta-analysis aimed to summarise and evaluate the overflow effects of interventions targeting a single behaviour (physical activity, sedentary behaviour/screen time, or sleep) on other non-targeted behaviours among children and adolescents.MethodsSix databases (MEDLINE [Ovid], PsycINFO [ProQuest], EMBASE [Ovid], PubMed, Web of Science and SPORTDiscus [EBSCO]) were searched for relevant studies published before 13 May, 2024. Randomised controlled trials and clustered randomised controlled trials that targeted a single behaviour and also assessed the effects on non-targeted behaviours, comprised of healthy children under the age of 18 years, were included. Movement behaviours can be measured either objectively or subjectively. The revised Cochrane risk-of-bias tool for randomised trials was adopted to evaluate the risk of bias.ResultsA total of 102 studies with 45,998 participants from 21 countries were identified, and 60 of them with 26,183 participants were incorporated into the meta-analysis. The meta-analysis demonstrated that physical activity interventions led to a reduction in the proportion of each day spent in sedentary behaviour (mean difference = - 0.95% of wear time, 95% confidence interval - 1.44, - 0.45, I2 = 39%). Sedentary behaviour interventions resulted in increased standing time (mean difference = 3.87%, 95% confidence interval 1.99, 5.75, I2 = 0%). Interventions targeting screen time did not yield changes in physical activity or sleep. The findings on the effectiveness of sleep interventions on non-targeted behaviours and of physical activity interventions on sleep were inconclusive.ConclusionsOverall, the findings suggested that interventions aimed at increasing physical activity or reducing sedentary behaviour had overflow effects on non-targeted behaviours, but the effect sizes were small. Additional evidence is needed to reach definitive conclusions regarding the impact of behaviour change interventions on sleep and of the overflow effects of sleep interventions.

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Patterns of interest change in stack overflow.

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Patterns of interest change in stack overflow.

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