What 3.3 Million Zhihu Users Reveal About Gender, Location, and Careers
Analyzing over 3.2 million publicly available Zhihu profiles collected via a distributed Python crawler, this report uncovers gender balance near 1:1, top residential cities, dominant occupations, university participation, and the most followed and active contributors, while noting data limitations and temporal relevance.
The author used a distributed Python crawler to collect 3,289,329 public Zhihu user profiles in July 2017. After deduplication, the dataset contains over 3.2 million records. Analysis was performed with ElasticSearch and Kibana.
Gender Ratio
The gender distribution is close to 1:1, with males slightly ahead.
Male: 1,202,234 (51.55%)
Female: 1,129,874 (48.45%)
Geographic Distribution
Users are concentrated in first‑tier cities, especially Beijing and Shanghai. The top ten residential cities are Beijing, Shanghai, Hangzhou, Chengdu, Nanjing, Wuhan, Guangzhou, Shenzhen, Xi'an, and Chongqing.
Occupation Distribution
Students dominate the user base. Excluding students, the top ten occupations are Product Manager, Freelancer, Programmer, Engineer, Designer, Tencent employee, Teacher, HR, Operations, and Lawyer.
University Users
Students come from many universities; the most represented are Zhejiang University, Wuhan University, Huazhong University of Science and Technology, Sun Yat‑sen University, Peking University, Shanghai Jiao‑Tong University, Fudan University, Nanjing University, Sichuan University, and Tsinghua University.
Top Zhihu Influencers
By total likes, the top 100 users are shown in a word‑cloud; the most liked user is Zhang Jiawei with over 3.6 million likes. By follower count, the top 10 include Zhang Jiawei, Li Kaifu, Huang Jixin, Zhou Yuan, and others.
Answer Activity vs. Likes
There is little correlation between the number of answers a user provides and the total likes they receive; quality appears more important than quantity.
Live Participation
The most active participants in Zhihu Live sessions have attended over 1,600 events, indicating high engagement.
Conclusion
This simple analysis of 3 million Zhihu profiles highlights gender balance, geographic concentration, dominant occupations, university representation, and the most influential contributors, while acknowledging data incompleteness and temporal constraints.
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