The Trans News Initiative is a collaborative effort to track news coverage of trans communities over time. A streamgraph shows article counts by topic, between 2020 and the present and clicking through shows a set of packed circles and tables that link to each article.
On the classification of articles:
Wire stories published by multiple outlets were treated as individual articles instead of collapsed, prioritizing news dissemination and reach over unique reporting. Generic news round-ups and recaps (e.g., “Weekend Report”, “Top Stories”, “News Roundup”) were filtered from the event data. We then used the RoBERTa-base model to assign embeddings to each article headline, and employed these embeddings to cluster the output using HDBSCAN. The clusters were labelled using an LLM aimed at creating an umbrella cluster phrase from the individual article headlines in the same cluster.
This system was used to identify themes, which again, you can see over time.
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