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  license: cc
 
 
 
 
 
 
 
 
 
 
 
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  license: cc
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+ task_categories:
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+ - text-classification
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+ language:
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+ - en
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+ tags:
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+ - tweet-classification
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+ - topic-detection
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+ - topic-classification
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+ - topics
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+ - tweets
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+ - tweet-length
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  ---
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+
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+ Published tweet dataset used in "Tweet Length Matters: A Comparative Analysis on Topic Detection in Microblogs" includes tweet id and corresponding topic number.
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+
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+ Topic numbers encoded as follows:
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+
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+ Topic Topic Number
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+ BLM Movement 0
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+ Covid-19 1
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+ K-Pop 2
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+ Bollywood 3
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+ Gaming 4
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+ U.S. Politics 5
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+ Out-of-Topic 6
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+
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+ In total, there are 354,310 tweet instances.
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+
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+ More details can be found at https://github.com/avaapm/ECIR2021/
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+
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+ Citation
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+
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+ If you make use of these tools, please cite following paper.
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+
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+ @inproceedings{DBLP:conf/ecir/SahinucT21,
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+ author = {Furkan {\c{S}}ahinu{\c{c}} and Cagri Toraman},
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+ title = {Tweet Length Matters: {A} Comparative Analysis on Topic Detection in Microblogs},
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+ booktitle = {Advances in Information Retrieval - 43rd European Conference on {IR} Research, {ECIR} 2021, Virtual Event, March 28 - April 1, 2021, Proceedings, Part {II}},
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+ series = {Lecture Notes in Computer Science},
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+ volume = {12657},
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+ pages = {471--478},
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+ publisher = {Springer},
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+ year = {2021},
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+ url = {https://doi.org/10.1007/978-3-030-72240-1\_50},
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+ doi = {10.1007/978-3-030-72240-1\_50},
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+ }