Abstract: We present LEDS, a framework for discovering and summarizing local events in Twitter streams. LEDS integrates spatiotemporal clustering with keyword extraction to detect event candidates, then applies summarization (centroid-based ranking + language-model scoring) to generate concise descriptions. Evaluation on real tweets shows superior recall and summary quality compared to baselines.
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