This study develops a Depression Corpus with over 4.4 million tokens sourced from 5,167 threads and 20,783 posts in an online depression forum, utilizing R and RStudio for data collection. It investigates how individuals express emotions and construct narratives about depression in digital health communication. By employing a methodological framework combining corpus linguistics and critical discourse analysis, the research utilizes tools such as Wmatrix4, Sketch Engine, and Wordsmith to explore semantic patterns within depression discourse. The analysis reveals key emotional constructs, enhancing understanding of both negative and positive sentiments related to mental health. This research contributes to improved recognition and support strategies for individuals experiencing depression, fostering a deeper comprehension of their experiences through linguistic analysis. Ultimately, it underscores the value of linguistic approaches in addressing complex psychological health issues.
Peiwen Zhang (Mon,) studied this question.