Create README.md
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README.md
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---
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language:
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- en
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- tl
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tags:
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- politics
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- social-media
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- tiktok
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- hate-speech
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- antisemitism
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pretty_name: Widespread Antisemitism on TikTok
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---
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## Summary
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This dataset contains TikTok comments and replies identified as antisemitic. This dataset contains metadata about each comment, such as user profile, engagement metrics, and geographical data, to support comprehensive analysis.
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## Date Fields
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The dataset is structured as a CSV file with the following columns:
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`post_id`: Unique numerical identifier for the TikTok post
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`comment_id`: Unique numerical identifier for the comment or reply
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`parent_id`: Reference to the `comment_id` of the comment that this comment is replying to
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`username`: Unique identifier for the user who published the comment or reply
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`nickname`: Display name of the user who published the comment or reply
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`bio`: Bio or description of the user who published the comment or reply
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`avatar`: URL that points to the avatar associated with the user's profile
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`text`: Full text of the comment or reply
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`region`: Geographical region where the user published the comment or reply
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`likes`: Number of likes that the comment or reply received
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`reply_count`: Number of replies that the comment or reply generated
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`liked_by_creator`: Boolean indicating whether the post author "liked" the comment or reply
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`created`: Timestamp when the comment or reply was published
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## Dataset Creation
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1. **Data Collection**: data collection via the TikTok API, focusing on post interactions
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2. **Keyword Filtering**: User interactions such as comments and replies, and user profile information such as nicknames and descriptions were filtered using three distinct keywords groups:
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1. **Israel-related symbols**: Emojis such as the Israel flag (🇮🇱) and the Star of David (✡️) were used to identify relevant content and possible misuses
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2. **Yellow Ribbon**: The yellow ribbon emoji (🎗️), a symbol of hope and support for those who are held in captivity, was also included to identify relevant content
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3. **Antisemetic Keywords**: Specific keywords and phrases commonly associated with antisemitism were used to filter and identify content with antisemetic undertones
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3. **Data scraping**: Comments, replies, and user profile information identified to contain antisemetic content were subjected to targeted data scraping to collect detailed information, including the whole thread history and user profile metadata.
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## Limitations
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This dataset only includes text-based content from user interactions and user profiles. This dataset does not include photo or video content.
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