## 5 The Model Application to Real-World Reddit Posts and Comments
### The Model Application to Pools of Comments  
As stated above, for social media analysis, it is crucial to have a possibility to summarize pools of user posts and/or comments. Thus, we have conducted tests on a collection of comments from the abovementioned collection of posts. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Post Title** & **User Summary** & **Automated Summary** \\ \hline A dark part of WallStreetBets history, and why it’s important for you to know and remember & Founder bad, greedy, got banned for being greedy. Being greedy again with new sub. & Founder bad, greedy, got banned for being greedy. banned for being greedy. Being greedy again with new begin with new spotlight on the good mds. u/Speaks and post posts. \\ \hline I suspect the hedgies are illegally covering their short positions & [PERSON][PERSON] and gang hasn’t covered shit. They’ve been illegally “closing out”” their short positions and if we hold they will 100\% get fucked. There is far more nefarious shit at play.** & There is far more nefarious shit at play.** & There is far more nefarious shit at play.** & So this morning I saw the S3 and put into the SEC has been for a long time, but it’s not worth it. \\ \hline \hline \end{tabular}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} The real reason Wall Street is terrified of the GME situation & We probably own way more of GME than we think and that is freaking out Wall Street because it could prove they’ve been up to some extremely illegal shit and the whole system could implode as a result. \\ \hline Can you say “CLASS ACTION LAWSUIT”. Fuck you RobinHood & GME to 1000 EOD, GME 5000 EONW. THE SUQEEZE HAS NOT SQUOZEN YET, BUY AND HOLD & I hate autism. I think it’s a bad idea. \\ \hline Upvote to ban all of Canada from the internet & \#CanaBan2017 & CanaBan2017201720172017.com 2016s 2011–2007 and 2012–2007’s last year. \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Examples of post summaries with TL;DRs. The test sub-dataset of comments was collected on the basis of their popularity. As the model we applied had a limitation of working best with the 512-token texts, we had to limit the length of each pool; this limitation was not relevant for posts, most of which were shorter, but it was crucial for the comment pools (see Figure 4 for the length distribution in the sub-datasets of posts and comment pools). Due to their high volume and the model limitations, the collection of comments had the following logic. First, we uploaded the top popular 30% of all comments per post, without additional subsequent answers to comments. Even after this, as Figure 4 demonstrates, the average length of comment pools subjected to summarization was ~4000 words, instead of ~150+ words for the posts. Thus, only the most popular comments of the 30% pools that fitted to the 512-token limitation were summarized. On the comments, the fine-tuned model has, in general, shown stronger results than the non-fine-tuned model, and the baseline threshold of 512 tokens was, technically, not an issue. This means that abstractive summarization can be directly applied to summarize pools of user texts, e.g., the posts/comments by one author, discussion threads, or topic-related pools previously discovered by topic modeling techniques. Human assessment has shown that some comment summaries are capable of capturing both the topicality of the post and the general mood of commenters, e.g., their opposition to the author (see Table 5, line 1, the post on prices of shares), just as their shared sentiment with the author of the post (see Table 5, line 2, the post on wage wars). The comments also had some grammar structures typical for argumentation ('This is not about the market, it's about how much you are willing to pay attention to your own product', see Table 5, line 1). Examples of comment summaries may also be found in Appendix A. However, this was the case in less than 50% cases.