Exploring Online Depression Forums via Text Mining: A Comparison of R eddit and a Curated Online Forum (2020)

Abstract: We present a study employing various techniques of text mining to explore and compare two different online forums focusing on depression: (1) the subreddit r/depression (over 60 million tokens), a large, open social media platform and (2) Beyond Blue (almost 5 million tokens), a professionally curated and moderated depression forum from Australia. We are interested in how the language and the content on these platforms differ from each other. We scrape both forums for a specific period. Next to general methods of computational text analysis, we focus on sentiment analysis, topic modeling and the distribution of word categories to analyze these forums. Our results indicate that Beyond Blue is generally more positive and that the users are more supportive to each other. Topic modeling shows that Beyond Blue’s users talk more about adult topics like finance and work while topics shaped by school or college terms are more prevalent on r/depression. Based on our findings we hypothesize that the professional curation and moderation of a depression forum is beneficial for the discussion in it.

## introduction in recent years, online forums and communities have become an important outlet for growing numbers of people who struggle with depression. for example, the subreddit r/depression on reddit had a growth from around 100,000 members in 2015 to over 570,000 in 2020 1 . while a few decades ago, affected would have had to find support or self-help groups in their local area, they are now able to talk about depression and share their stories with thousands of like minded individuals from the comfort of their own home. besides r/depression, there are traditional forums focusing on mental health that offer people a place to talk about their condition. some of these are professionally curated as well, providing support hotlines, ties to experts in psychiatry and further articles on important topics. in the following paper, we want to investigate how language and content of a platform like r/depression differs from a traditional and professionally accompanied forum and how we can explore these questions with the support of text mining methods. specifically, we compare content and language through various text mining methods, using word frequencies, topic modeling, word categories as well as sentiment analysis. we regard the project at the moment as descriptive and explorative, therefore we do not want to validate concrete hypothesis but rather explore methods and data to formulate potential hypotheses for future work. while there is research applying computational text analysis on depression forums, we are not aware of similar research focusing on the comparison of a curated and a non-curated forum. ## limitations we want to highlight some of the major limitations of our project. the striking problem is that both corpora differ largely from each other, predominantly considering the size. we tried to control this limitation to some extent by (1) focusing on normalized metrics for our methods and (2) including at least a year for r/depression to avoid seasonal changes and to reduce the size of r/depression. the demographic of the user base might differ as well. beyond blue is a predominantly australian forum while r/depression is constituted by a more international user base. while statistics show that reddit's user base is primarly male and young foot_5 , certain results point to a more adult user base for beyond blue (althoug we have no concrete statistics). r/depression has also no moderation by trained professionals. we address further differences between the user base in the upcoming chapter. another important limitation lies in the application of some of the methods. the results of the sentiment analysis have to be taken with caution. while vader is optimized for social media content, we did not precisely evaluate the performance on these specific corpora. while the liwc dictionary is an established resource for lexical analysis, it is also not specifically designed for social media content and might therefore lack some important terms or categories. ## discussion please not that due to the fact that we gathered publicly available data and we only deal with anonymized data, we did not need permission by the ethics commission of our institution at the time of the writing. first, we want to highlight similarities between both forums, which might point to general attributes of depression forums and their users: in both forums time-related terms are among the most frequent ones, showing that the narration of past and present events is a consistent discussion in depression forums. both forums show a tendency to positive sentiment, thus illustrating that support and the recollection of positive aspects are an important part of depression forums in general. topics about relationships, family, work and medication are highly important in both forums and structured rather similar. especially the consistency considering the topics about relationships and family show the importance of these aspects for depressive illnesses. considering differences of the two forums, our findings correlate well and support assumptions over all applied methods. general corpus analysis and analysis about word categories conducted with liwc show that the posts in general, as well as the language in beyond blue revolve around support and positivity, whereas negative speech and posts with little information value are more common in r/depression. this is in line with the finding that the answers to posts are much longer on average in beyond blue than in r/depression pointing to a more seriously engaged user and moderator base. the sentiment scores support this impression with beyond blue being noticeably more positive, mainly because answers to initial submissions in r/depression have a more negative sentiment than the rather positive responses on beyond blue. the findings produced by the topic modeling approach include the impression that the user base of beyond blue is older, as some topics have a focus on financial and organizational themes, and indicate a "parent view" while r/depression's users speak about school, college and their parents. most interestingly, and complementing other findings, topics dealing with self-harm and suicide can be found in both forums but are considerably more support oriented in beyond blue and more emotional and negatively biased in r/depression. concluding, beyond blue and r/depression seem to have different focal points. where beyond blue's support oriented language and content seems to indicate conversations where concrete problems are solved, r/depression's emotional posts, past tense and rather negative sentiment imply the focus lies on sharing experiences and converse about emotions. while our findings are exploratory at the moment, we hypothesize that a professionally curated and smaller forum might be more beneficial to be used by persons affected by depression since it is more supportive and positive in its content. this conclusion has to be taken with caution because (1) many differences might rely on the different user demographic, which seems to be younger in r/depression and (2) the open and more peer-oriented culture of reddit might still be helpful and beneficial in some situations. there are certain approaches we want to pursue to further investigate our results. we want to create a more balanced corpus by acquiring a collection of similar forums like beyond blue instead of just one. it is also necessary to optimize several of our text mining techniques for our context. lastly, we also plan to work closely with professional psychologists and therapists to integrate their expertise into our project.