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2020 | OriginalPaper | Buchkapitel

EveSense: What Can You Sense from Twitter?

verfasst von : Zafar Saeed, Rabeeh Ayaz Abbasi, Imran Razzak

Erschienen in: Advances in Information Retrieval

Verlag: Springer International Publishing

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Abstract

Social media has become a useful source for detecting real-life events. This paper presents an event detection application EveSense. It detects real-life events and related trending topics from the Twitter stream and allows users to find interesting events that have recently occurred. It uses a novel Dynamic Heartbeat Graph (DHG) approach, which efficiently extracts distinguishing features and performs better than the existing event detection methods. We tested and evaluated the application on three case studies, including a sports event (FA cup Final) and two political events (Super Tuesday and US Election).

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Fußnoten
1
Event detection approach, and performance comparison with existing approaches are available in [79].
 
3
The detail about feature design can be found in our previous studies [7, 8].
 
Literatur
1.
Zurück zum Zitat Aiello, L.M., et al.: Sensing trending topics in Twitter. IEEE Trans. Multimedia 15(6), 1268–1282 (2013)CrossRef Aiello, L.M., et al.: Sensing trending topics in Twitter. IEEE Trans. Multimedia 15(6), 1268–1282 (2013)CrossRef
2.
Zurück zum Zitat Choi, H.-J., Park, C.H.: Emerging topic detection in twitter stream based on high utility pattern mining. Expert Syst. Appl. 115, 27–36 (2019)CrossRef Choi, H.-J., Park, C.H.: Emerging topic detection in twitter stream based on high utility pattern mining. Expert Syst. Appl. 115, 27–36 (2019)CrossRef
3.
Zurück zum Zitat Marcus, A., Bernstein, M.S., Badar, O., Karger, D.R., Madden, S., Miller, R.C.: TwitInfo: aggregating and visualizing microblogs for event exploration. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2011, pp. 227–236. ACM, New York (2011) Marcus, A., Bernstein, M.S., Badar, O., Karger, D.R., Madden, S., Miller, R.C.: TwitInfo: aggregating and visualizing microblogs for event exploration. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2011, pp. 227–236. ACM, New York (2011)
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Zurück zum Zitat Petrovic, S., Osborne, M., McCreadie, R., Macdonald, C., Ounis, I., Shrimpton, L.: Can Twitter replace newswire for breaking news? In: Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media, USA, pp. 713–716. AAAI Press, July 2013 Petrovic, S., Osborne, M., McCreadie, R., Macdonald, C., Ounis, I., Shrimpton, L.: Can Twitter replace newswire for breaking news? In: Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media, USA, pp. 713–716. AAAI Press, July 2013
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Zurück zum Zitat Rill, S., Reinel, D., Scheidt, J., Zicari, R.V.: PoliTwi: early detection of emerging political topics on Twitter and the impact on concept-level sentiment analysis. Knowl.-Based Syst. 69, 24–33 (2014)CrossRef Rill, S., Reinel, D., Scheidt, J., Zicari, R.V.: PoliTwi: early detection of emerging political topics on Twitter and the impact on concept-level sentiment analysis. Knowl.-Based Syst. 69, 24–33 (2014)CrossRef
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Zurück zum Zitat Saeed, Z., et al.: What’s happening around the world? A survey and framework on event detection techniques on Twitter. J. Grid Comput. 17(2), 279–312 (2019)CrossRef Saeed, Z., et al.: What’s happening around the world? A survey and framework on event detection techniques on Twitter. J. Grid Comput. 17(2), 279–312 (2019)CrossRef
7.
Zurück zum Zitat Saeed, Z., Abbasi, R.A., Razzak, I., Maqbool, O., Sadaf, A., Xu, G.: Enhanced heartbeat graph for emerging event detection on Twitter using time series networks. Expert Syst. Appl. 136, 115–132 (2019)CrossRef Saeed, Z., Abbasi, R.A., Razzak, I., Maqbool, O., Sadaf, A., Xu, G.: Enhanced heartbeat graph for emerging event detection on Twitter using time series networks. Expert Syst. Appl. 136, 115–132 (2019)CrossRef
8.
Zurück zum Zitat Saeed, Z., Abbasi, R.A., Razzak, M.I., Xu, G.: Event detection in Twitter stream using weighted dynamic heartbeat graph approach. IEEE Comput. Intell. Mag. 14(3), 29–38 (2019)CrossRef Saeed, Z., Abbasi, R.A., Razzak, M.I., Xu, G.: Event detection in Twitter stream using weighted dynamic heartbeat graph approach. IEEE Comput. Intell. Mag. 14(3), 29–38 (2019)CrossRef
9.
Zurück zum Zitat Saeed, Z., Abbasi, R.A., Sadaf, A., Razzak, M.I., Xu, G.: Text stream to temporal network - a dynamic heartbeat graph to detect emerging events on Twitter. In: Phung, D., Tseng, V.S., Webb, G.I., Ho, B., Ganji, M., Rashidi, L. (eds.) PAKDD 2018. LNCS (LNAI), vol. 10938, pp. 534–545. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93037-4_42CrossRef Saeed, Z., Abbasi, R.A., Sadaf, A., Razzak, M.I., Xu, G.: Text stream to temporal network - a dynamic heartbeat graph to detect emerging events on Twitter. In: Phung, D., Tseng, V.S., Webb, G.I., Ho, B., Ganji, M., Rashidi, L. (eds.) PAKDD 2018. LNCS (LNAI), vol. 10938, pp. 534–545. Springer, Cham (2018). https://​doi.​org/​10.​1007/​978-3-319-93037-4_​42CrossRef
Metadaten
Titel
EveSense: What Can You Sense from Twitter?
verfasst von
Zafar Saeed
Rabeeh Ayaz Abbasi
Imran Razzak
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-45442-5_64

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