Conclusion

The anime community on Reddit provides a platform for anime fans to openly communicate with each other, and a large number of users are active on the anime subreddit and its many franchise subreddits. We aim to analyze users’ activity in the community, such as post count, and various content features including common words, scores, content length, and content contractility. Our goal is to uncover the qualities of the anime community, understand content engagement, and explore factors influencing popularity. Analyzing content features like posting volume, common words, scores, content length, and content contractility can offer valuable insights into the anime community’s characteristics, content engagement, and overall popularity. This analysis aims to provide valuable insights for maintaining the community and serving as a reference for anime enthusiasts and practitioners in related industries.

We studied both the general ‘Anime’ subreddit, and various anime franchise subreddits. Anime subreddit participation in discussions shows an overall downward trend over time, though post counts have a small uptick when popular anime events occur. When broken down into specific franchises, there are different performances in terms of activity. Pokemon and One Piece have always maintained a high level of user activity. In addition to the overall change over time, our analysis also breaks down post counts by day of week and hour of date. It’s not surprising that weekend afternoons and evenings gather a lot of discussion, while lunch break time and afternoons on weekdays see a lot of discussion as well. What’s more, different franchises have their own unique active time periods, meaning that different franchise enthusiasts have different time preferences.

Analyzing text as a variable and conducting sentiment analysis allows us to have a better understanding of user engagement and topic discussions. Within the community that has 8.6 million members, the percentage of posts conveying positive and negative sentiments is roughly equal. Moreover, non-controversial posts are far more than controversial ones, indicating the overall harmonious atmosphere in the anime community. However, the sentiment analysis of popular anime series like ‘OnePiece’ and ‘Pokemon’ presents a different perspective, displaying less positive sentiments despite high discussion volumes. Despite the anime that has high volumes of discussion, this does not necessarily imply a more positive discussion within the community when compared to other anime. Overall, sentiment analysis showcases the intricate dynamics between fans and franchises, portraying a detailed relationship beyond mere discussion volumes.

The subreddit data was further analyzed using multiple machine learning models for predictive analytics to identify potential high levels of discussion, user engagement, and relevance to the animation industry’s financials. Submission scores and comment controversiality act as important indicators of popularity and discussion intensity. Predicting scores and controversiality based on various content features enables the assessment of whether a new submission or comment will trend and generate extensive discussion. It also offers a valuable starting point for predicting community engagement. Notably, the most influential features, comment count, and selftext length emphasize the significance of in-depth discussions or detailed content, positively impacting the overall score. Our investigation into anime also extends to the deeper relationship between fans’ conversations and franchises’ stock prices. Both linear regression and autoregressive integrated moving average (ARIMA) models showcased a complex non-linear relationship between subreddit metrics and stock prices. This intricate relationship suggests that fan participation on social media might not straightforwardly predict stock market trends, indicating potential influences from external factors in predicting stock prices. In short, machine learning models are utilized to predict engagement, scores, controversiality, and the intricate relationship between subreddit metrics and stock prices, revealing challenges in correlating social media with stock trends.

For future development on this topic, we could explore beyond fans’ talking to understand elements that trigger their emotions. This could involve other online platforms, not just limited to Reddit. We believe this broader scope could provide a more comprehensive view of the anime community. To address complex stock market issues, we contemplate widening our research scope, potentially considering significant news from entities like Nintendo and other leading franchises, as well as economic trends. Shifting from simplistic machine learning models, we might utilize more advanced techniques like neural networks to decipher possible intricate patterns. In summary, our project has already provided valuable insights into Reddit’s anime communities’ discussion patterns and connected to the stock market. With a more detailed analysis across diverse platforms, we anticipate discovering more perceptions about the dynamic impact of anime community and industry.