Analyzing the Human Recommendation Community 'ifyoulikeblank' on Reddit — Auxiliary materials
<p>This repository contains auxiliary materials for the iConference 2024 paper "“If I like BLANK, what else will I like?”: Analyzing<br>a Human Recommendation Community on Reddit" by Thi Binh Minh Cao and Toine Bogers (= corresponding author)</p> <p>Published in: <em>Proceedings of the 2024 iConference</em>, April 15--26, 2024, Changchun, China.</p> <p>The paper presents the results of an analysis of /r/ifyoulikeblank, a Reddit community dedicated to requesting and providing for recommendations. This repository contains the following auxiliary materials:</p> <ul> <li>The annotated sample of threads from the /r/ifyoulikeblank subreddit (<strong>annotated-dataset.xlsx</strong>). The second sheet in the Excel file explains the contents of the file.</li> <li>The R code for performing the analysis described in the paper (<strong>annotation-analysis.R</strong>)</li> <li>CSV file containing the genres attributed to the artists as crawled from the Spotify API (<strong>artist-spotify-genres.csv</strong>)</li> <li>CSV file containing the popularity scores crawled from the Spotify API for the seed items and Spotify recommendations (<strong>recommendation-popularity.reddit-vs-spotify.csv</strong>)</li> <li>CSV file containing the popularity scores crawled from the Spotify API for the Reddit (<strong>recommendation-popularity.reddit.csv</strong>)</li> <li>The stopwords file used in the textual analysis (<strong>stopwords.csv</strong>)</li> <li>Excel file containing the activity data for the /r/ifyoulikeblank subreddit (<strong>subreddit-stats.xlsx</strong>)</li> </ul>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 0