Authorship Analysis in Chinese Social Media Texts

This Element offers a fresh perspective on authorship analysis drawing on sentiment analysis.

This Element explores the sentiment and keyword features in both authorship profiling and authorship attribution in social media texts in the Chinese cultural context. This title is also available as Open Access on Cambridge Core.This Element explores the sentiment and keyword features in both authorship profiling and authorship attribution in social media texts in the Chinese cultural context. The key findings can be summarised as follows: firstly, sentiment scores and keyword features are distinctive in delineating authors' gender and age. Specifically, female and younger authors tend to be less optimistic and use more personal pronouns and graduations than male and older authors, respectively. Secondly, these distinctive profiling features are also distinctive and significant in authorship attribution. Thirdly, our mindset, shaped by our inherent hormonal influences and external social experiences, plays a critical role in authorship. Theoretically, the findings expand authorship features into underexplored domains and substantiate the theory of mindset. Practically, the findings offer some broad quantitative benchmarks for authorship profiling cases in the Chinese cultural context, and perhaps other contexts where authorship profiling analyses have been used. This title is also available as Open Access on Cambridge Core.