Instagram 2023-2024 Serie B Collective Emotions (First Round)
<p>The dataset contains collective emotional reactions extracted from user comments on Instagram posts from the 20 official Italian soccer teams competing in the 2023-24 Serie B (https://en.wikipedia.org/wiki/2023-24_Serie_B), the second tier of the Italian football league system.<br>Data spans from the day preceding the beginning of the championship, 15/08/2023, to the day following the conclusion of the first round, 27/12/2023.</p> <p>Emotional responses are categorized into four categories: anger, fear, joy, and sadness, inferred using "feel-it", a python library for emotion classification trained on Italian texts, to reconstruct the emotional content of users' comments. </p> <p>Each emotion has corresponding files:</p> <p>{values,barcodes}_{anger,fear,joy,sadness}.txt,</p> <p>whereas "values_anger.txt", for instance, contains the relative frequency of comments classified as conveying "anger" on a post, and "barcodes_anger.txt"<br>contains information indicating whether anger is a collective emotional reaction to a post (0 denotes absence/not relevant, 1 denotes maximal presence).</p> <p>In each file, the first column represents the name of the team's account, while the other columns represent the <br>values/barcodes of the target emotion across the teams' posting activities from 15/08/2023 to 27/12/2023.</p> <p>The dataset also includes:</p> <p>date_posts.txt: Timestamps for each post published by each team.<br>number_comments.txt: The number of classified comments, capped at 100 maximum comments.</p> <p>The dataset offers insights into the emotional dynamics and fandom engagement surrounding Serie B teams during the specified timeframe.<br>It was utilized to quantify burstiness and memory in collective emotional reactions.</p> <p>The process of emotion classification in user comments and the association of each post with an aggregate value/barcode constitutes an anonymization procedure ensuring that the original user comments cannot be traced.</p> <p> </p>
ShareScore
16/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 8
- Reuse readiness
- 0
- Engagement
- 0