Abstract
Twitter First Story Detection (FSD) task refers to the detection of first tweet about the new event in tweet stream, which is a hard but important task in twitter event detection. However, the number of comparisons is too large in traditional online detection methods and there is a lack of global information of each event during detection process. To deal with the shortcomings above, we propose a novel FSD method based on nugget, which can describe the event concisely. Our approach generates and updates dynamically a nugget for each detected event in the process of detection. When a new tweet arrives, it is first compared with the nugget of each event, to be clustered into the event when it hits the nugget. Otherwise it is compared with individual tweets in the event. Our method improves the detection accuracy and reduces the number of comparisons. The experimental results on two public data sets show that our system has reached the state-of-the-art. Besides, we prove theoretically that our method possesses advantages in efficiency.
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Notes
- 1.
A bucket contains some tweets about the same event which is detected already.
- 2.
ftp://jaguar.ncsl.nist.gov/current_docs/TDT3eval/TDT3fsd.pl.
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Qiu, Y., Li, S., Li, R., Wang, L., Wang, B. (2015). Nugget-Based First Story Detection in Twitter Stream. In: Zhang, X., Sun, M., Wang, Z., Huang, X. (eds) Social Media Processing. SMP 2015. Communications in Computer and Information Science, vol 568. Springer, Singapore. https://doi.org/10.1007/978-981-10-0080-5_7
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DOI: https://doi.org/10.1007/978-981-10-0080-5_7
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