A study of retrospective and on-line event detection
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Improving text categorization methods for event tracking
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Learning Approaches for Detecting and Tracking News Events
IEEE Intelligent Systems
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
A System for new event detection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Parameter free bursty events detection in text streams
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Analyzing feature trajectories for event detection
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Time-dependent event hierarchy construction
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering Using a Similarity Measure Based on Shared Near Neighbors
IEEE Transactions on Computers
Time is of the essence: improving recency ranking using Twitter data
Proceedings of the 19th international conference on World wide web
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
TwitterMonitor: trend detection over the twitter stream
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Streaming first story detection with application to Twitter
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Breaking News Detection and Tracking in Twitter
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
#TwitterSearch: a comparison of microblog search and web search
Proceedings of the fourth ACM international conference on Web search and data mining
Extracting events and event descriptions from Twitter
Proceedings of the 20th international conference companion on World wide web
Who says what to whom on twitter
Proceedings of the 20th international conference on World wide web
Do all birds tweet the same?: characterizing twitter around the world
Proceedings of the 20th ACM international conference on Information and knowledge management
Named entity recognition in tweets: an experimental study
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
TEDAS: A Twitter-based Event Detection and Analysis System
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
TwiNER: named entity recognition in targeted twitter stream
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Exploiting hybrid contexts for Tweet segmentation
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Who, where, when and what: discover spatio-temporal topics for twitter users
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 22nd international conference on World Wide Web companion
Social life networks: a multimedia problem?
Proceedings of the 21st ACM international conference on Multimedia
How the live web feels about events
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Predicting event-relatedness of popular queries
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Event detection from tweets is an important task to understand the current events/topics attracting a large number of common users. However, the unique characteristics of tweets (e.g. short and noisy content, diverse and fast changing topics, and large data volume) make event detection a challenging task. Most existing techniques proposed for well written documents (e.g. news articles) cannot be directly adopted. In this paper, we propose a segment-based event detection system for tweets, called Twevent. Twevent first detects bursty tweet segments as event segments and then clusters the event segments into events considering both their frequency distribution and content similarity. More specifically, each tweet is split into non-overlapping segments (i.e. phrases possibly refer to named entities or semantically meaningful information units). The bursty segments are identified within a fixed time window based on their frequency patterns, and each bursty segment is described by the set of tweets containing the segment published within that time window. The similarity between a pair of bursty segments is computed using their associated tweets. After clustering bursty segments into candidate events, Wikipedia is exploited to identify the realistic events and to derive the most newsworthy segments to describe the identified events. We evaluate Twevent and compare it with the state-of-the-art method using 4.3 million tweets published by Singapore-based users in June 2010. In our experiments, Twevent outperforms the state-of-the-art method by a large margin in terms of both precision and recall. More importantly, the events detected by Twevent can be easily interpreted with little background knowledge because of the newsworthy segments. We also show that Twevent is efficient and scalable, leading to a desirable solution for event detection from tweets.