2.5 Q3 Analyzing content - buy recommendations
[🔗Github Link]
We follow an approach used in a paper by Chacon et al (2022), where they try to study the effect of ‘buy’ recommendations in submissions in the r/WallStreetBets subreddit on actual stock performance. In the same approach, we generate a binary variable named buy_signal which is equal to 1 if the post contains one of these words: buy, bought, moon, hold, call, bull, like, moon, and yolo.
2.5.1. How do buy recommendations change as % of posts when activity increases in subreddits?
As the above time series plot shows, on average in 2022, usually around 10 and 25 % of posts in r/dogecoin and in r/cryptocurrency (those which mention dogecoin) contain words in the ‘buy words’ list defined above. However, this suddenly jumps during some periods like June - August 2022, when there were days in which more than 50% of posts/comments made by users had a ‘buy’ signal.
2.5.2. What is the average score of posts which contain buy signals for doge?
The average score of posts containing buy signals is much higher in both subreddits. The baseline levels are higher in r/dogecoin, reflecting the higher ingrained affiliation towards the coin. We confirm that the difference in scores is statistically significant by conducting a t-test between the samples, the results of which are given in the below table.
| Subreddit | Buy Signal Present | Mean Score | p-value |
|---|---|---|---|
| r/Dogecoin | No (0) | 56.03 | 4.37e-52 |
| r/Dogecoin | Yes (1) | 101.65 | 4.37e-52 |
| r/CryptoCurrency | No (0) | 30.08 | 0.000144 |
| r/CryptoCurrency | Yes (1) | 70.91 | 0.000144 |