Streaming First Story Detection with application to Twitter

By Sasa Petrovic, Miles Osborne, Victor Lavrenko. North American Chapter of the Association for Computational Linguistics, 2010

739 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8854ca5546396ef225112ec828094882a71fd01e

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Citations in the corpus

Sensing Trending Topics in Twitter (2013, methodology): “[22], which uses LSH to rapidly retrieve the nearest neighbour of a document and accelerate the clustering task.”
Discriminative Improvements to Distributional Sentence Similarity (2013, background): “Measuring the semantic similarity of short units of text is fundamental to many natural language processing tasks, from evaluating machine translation (Kauchak and Barzilay, 2006) to grouping redundant event mentions in social media (Petrovi´c et al., 2010).”
Semantics-driven Event Clustering in Twitter Feeds (2015, unknown): “Petrovi´c”
Open domain event extraction from twitter (2012, background): “Petrovi´c et al. investigate a streaming approach to identifying Tweets which are the .rst to report a breaking news story using Locally Sensitive Hash Functions [40].”
You Are What You Tweet: Analyzing Twitter for Public Health (2011, background): “Others have monitored the spread of news (Lerman and Ghosh 2010), detected the first mention of news events (Petrovi´c, Osborne, and Lavrenko 2010), and monitored earthquakes (Sakaki, Okazaki, and Matsuo 2010).”
Twevent: segment-based event detection from tweets (2012, methodology): “The bursty feature extraction is then based on the perspective of statistics.”
Book Reviews: Data-Intensive Text Processing with MapReduce by Jimmy Lin and Chris Dyer (2010, methodology): “In the context of text processing, streaming algorithms have been applied to language modeling [90], translation modeling [89], and detecting the first mention of news event in a stream [121].”
Facebook, Twitter and Google Plus for Breaking News: Is There a Winner? (2014, methodology): “We considered additional events not in our Wikipedia list by running a state-of-the-art event detection system over data crawled over the same interval (Petrovic, Osborne, and Lavrenko 2010).”
Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation (2012, background): “Recent reports pointed out that Twitter messages can be indicative of real-world events (Petrovi´c et al., 2010; Sakaki et al., 2010).”
Learning similarity functions for topic detection in online reputation monitoring (2014, background): “In the last years, topic and event detection in Twitter has also become a very active research area [32, 29].”