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Male and Female Users' Differences in Online Technology Community Based on Text Mining
Bing Sun1, Hongying Mao1, Chengshun Yin1
1School of Economics and Management, Harbin Engineering University, Harbin, China.
Frontiers in Psychology
|June 13, 2020
Summary
Male users in tech communities often provide help, while females focus on socializing and advertising. Both genders express positivity, but females show it more, influencing their activity.
Area of Science:
- Computer-Mediated Communication
- Social Computing
- Gender Studies
Background:
- Online technology communities are increasingly popular for personalized learning.
- Understanding user behavior differences is crucial for community engagement.
Purpose of the Study:
- To investigate gender-based behavioral differences in online technology communities.
- To analyze topic preferences, sentiment, and activity levels of male and female users.
Main Methods:
- Latent Dirichlet Allocation (LDA) for topic modeling.
- Sentiment analysis to gauge emotional tendencies.
- Regression analysis to assess activity correlations.
Main Results:
- Male users predominantly engage in information-seeking/providing, while female users focus on social interaction and advertising.
- Both genders exhibit positive sentiment, with females expressing it more frequently.
- Emotional orientation significantly impacts user activity, particularly for female users.
Conclusions:
- Gender influences participation patterns and communication styles in online tech communities.
- Sentiment plays a critical role in driving user engagement, especially for women.
- These findings can inform strategies for fostering inclusive and active online learning environments.
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