Skip to main content
Erschienen in: International Journal of Data Science and Analytics 4/2022

10.06.2022 | Review

A survey on event and subevent detection from microblog data towards crisis management

verfasst von: Shatadru Roy Chowdhury, Srinka Basu, Ujjwal Maulik

Erschienen in: International Journal of Data Science and Analytics | Ausgabe 4/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Social media data analysis is a popular research domain since the last decade. Detecting the events and sub-events from social media posts that require special attention is one of the key research problem in this domain with wide range of applications. Particularly in the field of crisis management, event and sub-event detection can be of great benefit assisting the public safety departments to plan for quick responses. In this paper, we review the existing researches in the field of event and sub-event identification from social media based microblog data for disaster management. The contribution of the paper includes the study of research papers from two different aspects - i) Computational Steps for performing a research on event and sub-event detection from social media data, ii) Computational Techniques briefly discussing the methods adopted in recent studies pertaining to event and sub-event detection and summarization. This study would help the future researches in the social media data analytics domain for crisis management.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Abhik, D., Toshniwal, D.: Sub-event detection during natural hazards using features of social media data. In: Proceedings of the 22nd International Conference on World Wide Web, WWW ’13 Companion, pp. 783–788. Association for Computing Machinery, New York, NY, USA (2013). https://doi.org/10.1145/2487788.2488046 Abhik, D., Toshniwal, D.: Sub-event detection during natural hazards using features of social media data. In: Proceedings of the 22nd International Conference on World Wide Web, WWW ’13 Companion, pp. 783–788. Association for Computing Machinery, New York, NY, USA (2013). https://​doi.​org/​10.​1145/​2487788.​2488046
3.
Zurück zum Zitat Adedoyin-Olowe, M., Gaber, M.M., Stahl, F.: Trcm: A methodology for temporal analysis of evolving concepts in twitter. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) Artificial Intelligence and Soft Computing, pp. 135–145. Springer, Berlin Heidelberg (2013)CrossRef Adedoyin-Olowe, M., Gaber, M.M., Stahl, F.: Trcm: A methodology for temporal analysis of evolving concepts in twitter. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) Artificial Intelligence and Soft Computing, pp. 135–145. Springer, Berlin Heidelberg (2013)CrossRef
4.
Zurück zum Zitat Afyouni, I., Khan, A.S., Aghbari, Z.A.: Spatio-temporal event discovery in the big social data era. In: Proceedings of the 24th Symposium on International Database Engineering & Applications, IDEAS ’20. Association for Computing Machinery, New York, NY, USA (2020). https://doi.org/10.1145/3410566.3410568 Afyouni, I., Khan, A.S., Aghbari, Z.A.: Spatio-temporal event discovery in the big social data era. In: Proceedings of the 24th Symposium on International Database Engineering & Applications, IDEAS ’20. Association for Computing Machinery, New York, NY, USA (2020). https://​doi.​org/​10.​1145/​3410566.​3410568
6.
Zurück zum Zitat Akbari, M., Hu, X., Liqiang, N., Chua, T.S.: From tweets to wellness: Wellness event detection from twitter streams. In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, AAAI’16, pp. 87–93. AAAI Press (2016) Akbari, M., Hu, X., Liqiang, N., Chua, T.S.: From tweets to wellness: Wellness event detection from twitter streams. In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, AAAI’16, pp. 87–93. AAAI Press (2016)
7.
Zurück zum Zitat Aktunc, R., Toroslu, I., Karagoz, P.: Event detection by change tracking on community structure of temporal networks. In: 2018 IEEE/ACM Int. Conf. on Advances in Social Networks Analysis and Mining (ASONAM), pp. 928–931. IEEE Computer Society, Los Alamitos, CA, USA (2018). https://doi.org/10.1109/ASONAM.2018.8508325 Aktunc, R., Toroslu, I., Karagoz, P.: Event detection by change tracking on community structure of temporal networks. In: 2018 IEEE/ACM Int. Conf. on Advances in Social Networks Analysis and Mining (ASONAM), pp. 928–931. IEEE Computer Society, Los Alamitos, CA, USA (2018). https://​doi.​org/​10.​1109/​ASONAM.​2018.​8508325
11.
Zurück zum Zitat Alsaedi, N., Burnap, P.: Feature extraction and analysis for identifying disruptive events from social media. In: Proceedings of the 2015 IEEE/ACM Int. Conf. on Advances in Social Networks Analysis and Mining 2015, ASONAM ’15, pp. 1495–1502. Association for Computing Machinery, New York, NY, USA (2015). https://doi.org/10.1145/2808797.2808867 Alsaedi, N., Burnap, P.: Feature extraction and analysis for identifying disruptive events from social media. In: Proceedings of the 2015 IEEE/ACM Int. Conf. on Advances in Social Networks Analysis and Mining 2015, ASONAM ’15, pp. 1495–1502. Association for Computing Machinery, New York, NY, USA (2015). https://​doi.​org/​10.​1145/​2808797.​2808867
12.
Zurück zum Zitat Alsaedi, N., Burnap, P., Rana, O.: Identifying disruptive events from social media to enhance situational awareness. In: 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 934–941 (2015). https://doi.org/10.1145/2808797.2808879 Alsaedi, N., Burnap, P., Rana, O.: Identifying disruptive events from social media to enhance situational awareness. In: 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 934–941 (2015). https://​doi.​org/​10.​1145/​2808797.​2808879
16.
Zurück zum Zitat Anam, M., Shafiq, B., Shamail, S., Chun, S.A., Adam, N.: Discovering events from social media for emergency planning. In: Proceedings of the 20th Annual International Conference on Digital Government Research, dg.o 2019, p. 109–116. Association for Computing Machinery, New York, NY, USA (2019). https://doi.org/10.1145/3325112.3325213 Anam, M., Shafiq, B., Shamail, S., Chun, S.A., Adam, N.: Discovering events from social media for emergency planning. In: Proceedings of the 20th Annual International Conference on Digital Government Research, dg.o 2019, p. 109–116. Association for Computing Machinery, New York, NY, USA (2019). https://​doi.​org/​10.​1145/​3325112.​3325213
17.
Zurück zum Zitat Ansah, J., Kang, W., Liu, L., Liu, J., Li, J.: Sensortree: Bursty propagation trees as sensors for protest event detection. In: Hacid, H., Cellary, W., Wang, H., Paik, H.Y., Zhou, R. (eds.) Web Information Systems Engineering - WISE 2018, pp. 281–296. Springer International Publishing, Cham (2018)CrossRef Ansah, J., Kang, W., Liu, L., Liu, J., Li, J.: Sensortree: Bursty propagation trees as sensors for protest event detection. In: Hacid, H., Cellary, W., Wang, H., Paik, H.Y., Zhou, R. (eds.) Web Information Systems Engineering - WISE 2018, pp. 281–296. Springer International Publishing, Cham (2018)CrossRef
19.
Zurück zum Zitat Arbib, M.: The Handbook of Brain Theory and Neural Network, vol. 26 (2003) Arbib, M.: The Handbook of Brain Theory and Neural Network, vol. 26 (2003)
23.
Zurück zum Zitat Bekoulis, G., Deleu, J., Demeester, T., Develder, C.: Sub-event detection from twitter streams as a sequence labeling problem. CoRR abs/1903.05396 (2019) Bekoulis, G., Deleu, J., Demeester, T., Develder, C.: Sub-event detection from twitter streams as a sequence labeling problem. CoRR abs/1903.05396 (2019)
27.
Zurück zum Zitat Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. JMLR 3, 993–1022 (2003) Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. JMLR 3, 993–1022 (2003)
30.
Zurück zum Zitat Chen, C., Terejanu, G.: Sub-event detection on twitter network. In: Iliadis, L., Maglogiannis, I., Plagianakos, V. (eds.) Artificial Intelligence Applications and Innovations, pp. 50–60. Springer International Publishing, Cham (2018)CrossRef Chen, C., Terejanu, G.: Sub-event detection on twitter network. In: Iliadis, L., Maglogiannis, I., Plagianakos, V. (eds.) Artificial Intelligence Applications and Innovations, pp. 50–60. Springer International Publishing, Cham (2018)CrossRef
31.
33.
Zurück zum Zitat Chen, G., Xu, N., Mao, W.: An encoder-memory-decoder framework for sub-event detection in social media. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM ’18, pp. 1575–1578. Association for Computing Machinery, New York, NY, USA (2018). https://doi.org/10.1145/3269206.3269256 Chen, G., Xu, N., Mao, W.: An encoder-memory-decoder framework for sub-event detection in social media. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM ’18, pp. 1575–1578. Association for Computing Machinery, New York, NY, USA (2018). https://​doi.​org/​10.​1145/​3269206.​3269256
34.
Zurück zum Zitat Chen, J., Shang, Q., Xiong, H.: Hot events detection for chinese microblogs based on the th-lda model. In: Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018), pp. 157–166. Atlantis Press (2018/12). https://doi.org/10.2991/tlicsc-18.2018.26 Chen, J., Shang, Q., Xiong, H.: Hot events detection for chinese microblogs based on the th-lda model. In: Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018), pp. 157–166. Atlantis Press (2018/12). https://​doi.​org/​10.​2991/​tlicsc-18.​2018.​26
45.
Zurück zum Zitat Fedoryszak, M., Frederick, B., Rajaram, V., Zhong, C.: Real-time event detection on social data streams. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’19, pp. 2774–2782. Association for Computing Machinery, New York, NY, USA (2019). https://doi.org/10.1145/3292500.3330689 Fedoryszak, M., Frederick, B., Rajaram, V., Zhong, C.: Real-time event detection on social data streams. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’19, pp. 2774–2782. Association for Computing Machinery, New York, NY, USA (2019). https://​doi.​org/​10.​1145/​3292500.​3330689
46.
Zurück zum Zitat Feng, W., Zhang, C., Zhang, W., Han, J., Wang, J., Aggarwal, C., Huang, J.: Streamcube: Hierarchical spatio-temporal hashtag clustering for event exploration over the twitter stream. In: 2015 IEEE 31st International Conference on Data Engineering, pp. 1561–1572 (2015). https://doi.org/10.1109/ICDE.2015.7113425 Feng, W., Zhang, C., Zhang, W., Han, J., Wang, J., Aggarwal, C., Huang, J.: Streamcube: Hierarchical spatio-temporal hashtag clustering for event exploration over the twitter stream. In: 2015 IEEE 31st International Conference on Data Engineering, pp. 1561–1572 (2015). https://​doi.​org/​10.​1109/​ICDE.​2015.​7113425
47.
Zurück zum Zitat Gao, Y., Zhao, S., Yang, Y., Chua, T.S.: Multimedia social event detection in microblog. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MultiMedia Modeling, pp. 269–281. Springer International Publishing, Cham (2015)CrossRef Gao, Y., Zhao, S., Yang, Y., Chua, T.S.: Multimedia social event detection in microblog. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MultiMedia Modeling, pp. 269–281. Springer International Publishing, Cham (2015)CrossRef
50.
Zurück zum Zitat Gerner, D.J., Abu-Jabr, R., Schrodt, P.A., Yilmaz, Ö.: Conflict and mediation event observations (cameo): A new event data framework for the analysis of foreign policy interactions (2002) Gerner, D.J., Abu-Jabr, R., Schrodt, P.A., Yilmaz, Ö.: Conflict and mediation event observations (cameo): A new event data framework for the analysis of foreign policy interactions (2002)
51.
Zurück zum Zitat Goel, S., Ahuja, S., Subramanyam, A.V., Kumaraguru, P.: #visualhashtags: Visual summarization of social media events using mid-level visual elements. In: Proceedings of the 25th ACM International Conference on Multimedia, MM ’17, pp. 1434–1442. Association for Computing Machinery, New York, NY, USA (2017). https://doi.org/10.1145/3123266.3123407 Goel, S., Ahuja, S., Subramanyam, A.V., Kumaraguru, P.: #visualhashtags: Visual summarization of social media events using mid-level visual elements. In: Proceedings of the 25th ACM International Conference on Multimedia, MM ’17, pp. 1434–1442. Association for Computing Machinery, New York, NY, USA (2017). https://​doi.​org/​10.​1145/​3123266.​3123407
56.
Zurück zum Zitat Guo, B., Ouyang, Y., Zhang, C., Zhang, J., Yu, Z., Wu, D., Wang, Y.: Crowdstory: fine-grained event storyline generation by fusion of multi-modal crowdsourced data. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (2017). https://doi.org/10.1145/3130920 Guo, B., Ouyang, Y., Zhang, C., Zhang, J., Yu, Z., Wu, D., Wang, Y.: Crowdstory: fine-grained event storyline generation by fusion of multi-modal crowdsourced data. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (2017). https://​doi.​org/​10.​1145/​3130920
57.
Zurück zum Zitat Han, P., Zhou, N.: A framework for detecting key topics in social networks. In: Proceedings of the 2nd International Conference on Big Data Technologies, ICBDT2019, pp. 235–239. Association for Computing Machinery, New York, NY, USA (2019). https://doi.org/10.1145/3358528.3358540 Han, P., Zhou, N.: A framework for detecting key topics in social networks. In: Proceedings of the 2nd International Conference on Big Data Technologies, ICBDT2019, pp. 235–239. Association for Computing Machinery, New York, NY, USA (2019). https://​doi.​org/​10.​1145/​3358528.​3358540
61.
Zurück zum Zitat He, J., Liu, Y., Jia, Y.: Eventgraph based events detection in social media. In: Zhou, Q., Miao, Q., Wang, H., Xie, W., Wang, Y., Lu, Z. (eds.) Data Science, pp. 150–160. Springer Singapore, Singapore (2018)CrossRef He, J., Liu, Y., Jia, Y.: Eventgraph based events detection in social media. In: Zhou, Q., Miao, Q., Wang, H., Xie, W., Wang, Y., Lu, Z. (eds.) Data Science, pp. 150–160. Springer Singapore, Singapore (2018)CrossRef
65.
Zurück zum Zitat hu, L., Li, J., Nie, L., li, X., Shao, C.: What happens next? future subevent prediction using contextual hierarchical lstm. AAAI (2017) hu, L., Li, J., Nie, L., li, X., Shao, C.: What happens next? future subevent prediction using contextual hierarchical lstm. AAAI (2017)
72.
Zurück zum Zitat Jiang, S., Groves, W., Anzaroot, S., Jaimes, A.: Crisis sub-events on social media: a case study of wildfires (2019) Jiang, S., Groves, W., Anzaroot, S., Jaimes, A.: Crisis sub-events on social media: a case study of wildfires (2019)
77.
Zurück zum Zitat Kojima, S., Uchiyama, A., Shirakawa, M., Hiromori, A., Yamaguchi, H., Higashino, T.: Crowd and event detection by fusion of camera images and micro blogs. In: 2017 IEEE Int. Conf. on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 213–218 (2017). https://doi.org/10.1109/PERCOMW.2017.7917560 Kojima, S., Uchiyama, A., Shirakawa, M., Hiromori, A., Yamaguchi, H., Higashino, T.: Crowd and event detection by fusion of camera images and micro blogs. In: 2017 IEEE Int. Conf. on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 213–218 (2017). https://​doi.​org/​10.​1109/​PERCOMW.​2017.​7917560
82.
Zurück zum Zitat Li, J., Gao, W., Wei, Z., Peng, B., Wong, K.F.: Using content-level structures for summarizing microblog repost trees. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 2168–2178. Association for Computational Linguistics, Lisbon, Portugal (2015). https://doi.org/10.18653/v1/D15-1259 Li, J., Gao, W., Wei, Z., Peng, B., Wong, K.F.: Using content-level structures for summarizing microblog repost trees. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 2168–2178. Association for Computational Linguistics, Lisbon, Portugal (2015). https://​doi.​org/​10.​18653/​v1/​D15-1259
86.
Zurück zum Zitat Liu, Y., Zhou, B., Chen, F., Cheung, D.W.: Graph topic scan statistic for spatial event detection. In: Proceedings of the 25th ACM International Conference on Information and Knowledge Management, CIKM ’16, p. 489–498. Association for Computing Machinery, New York, NY, USA (2016). https://doi.org/10.1145/2983323.2983744 Liu, Y., Zhou, B., Chen, F., Cheung, D.W.: Graph topic scan statistic for spatial event detection. In: Proceedings of the 25th ACM International Conference on Information and Knowledge Management, CIKM ’16, p. 489–498. Association for Computing Machinery, New York, NY, USA (2016). https://​doi.​org/​10.​1145/​2983323.​2983744
87.
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 ’11, p. 227–236. Association for Computing Machinery, New York, NY, USA (2011). https://doi.org/10.1145/1978942.1978975 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 ’11, p. 227–236. Association for Computing Machinery, New York, NY, USA (2011). https://​doi.​org/​10.​1145/​1978942.​1978975
88.
Zurück zum Zitat McMinn, A.J., Jose, J.M.: Real-time entity-based event detection for twitter. In: J. Mothe, J. Savoy, J. Kamps, K. Pinel-Sauvagnat, G. Jones, E. San Juan, L. Capellato, N. Ferro (eds.) Experimental IR Meets Multilinguality, Multimodality, and Interaction, pp. 65–77. Springer International Publishing, Cham (2015) McMinn, A.J., Jose, J.M.: Real-time entity-based event detection for twitter. In: J. Mothe, J. Savoy, J. Kamps, K. Pinel-Sauvagnat, G. Jones, E. San Juan, L. Capellato, N. Ferro (eds.) Experimental IR Meets Multilinguality, Multimodality, and Interaction, pp. 65–77. Springer International Publishing, Cham (2015)
89.
Zurück zum Zitat Meladianos, P., Nikolentzos, G., Rousseau, F., Stavrakas, Y., Vazirgiannis, M.: Degeneracy-based real-time sub-event detection in twitter stream. In: ICWSM (2015) Meladianos, P., Nikolentzos, G., Rousseau, F., Stavrakas, Y., Vazirgiannis, M.: Degeneracy-based real-time sub-event detection in twitter stream. In: ICWSM (2015)
90.
Zurück zum Zitat Meladianos, P., Xypolopoulos, C., Nikolentzos, G., Vazirgiannis, M.: An optimization approach for sub-event detection and summarization in twitter. In: Pasi, G., Piwowarski, B., Azzopardi, L., Hanbury, A. (eds.) Advances in Information Retrieval, pp. 481–493. Springer International Publishing, Cham (2018)CrossRef Meladianos, P., Xypolopoulos, C., Nikolentzos, G., Vazirgiannis, M.: An optimization approach for sub-event detection and summarization in twitter. In: Pasi, G., Piwowarski, B., Azzopardi, L., Hanbury, A. (eds.) Advances in Information Retrieval, pp. 481–493. Springer International Publishing, Cham (2018)CrossRef
91.
Zurück zum Zitat Meng, X., Wang, P., Yan, H., Xu, L., Guo, J., Fan, Y.: Multi-graph convolution network with jump connection for event detection. In: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), pp. 744–751 (2019). https://doi.org/10.1109/ICTAI.2019.00108 Meng, X., Wang, P., Yan, H., Xu, L., Guo, J., Fan, Y.: Multi-graph convolution network with jump connection for event detection. In: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), pp. 744–751 (2019). https://​doi.​org/​10.​1109/​ICTAI.​2019.​00108
92.
Zurück zum Zitat Mihalcea, R., Tarau, P.: TextRank: Bringing order into text. In: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, pp. 404–411. Association for Computational Linguistics, Barcelona, Spain (2004) Mihalcea, R., Tarau, P.: TextRank: Bringing order into text. In: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, pp. 404–411. Association for Computational Linguistics, Barcelona, Spain (2004)
94.
Zurück zum Zitat Nair, M.R., Ramya, G., Sivakumar, P.B.: Usage and analysis of twitter during 2015 Chennai flood towards disaster management. In: Procedia Computer Science 115, 350–358 (2017). https://doi.org/10.1016/j.procs.2017.09.089. 7th International Conference on Advances in Computing and Communications, ICACC-2017, 22-24 August 2017, Cochin, India Nair, M.R., Ramya, G., Sivakumar, P.B.: Usage and analysis of twitter during 2015 Chennai flood towards disaster management. In: Procedia Computer Science 115, 350–358 (2017). https://​doi.​org/​10.​1016/​j.​procs.​2017.​09.​089. 7th International Conference on Advances in Computing and Communications, ICACC-2017, 22-24 August 2017, Cochin, India
98.
Zurück zum Zitat Orzechowski, P., Boryczko, K.: Text mining with hybrid biclustering algorithms. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) Artificial Intelligence and Soft Computing, pp. 102–113. Springer International Publishing, Cham (2016) Orzechowski, P., Boryczko, K.: Text mining with hybrid biclustering algorithms. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) Artificial Intelligence and Soft Computing, pp. 102–113. Springer International Publishing, Cham (2016)
101.
Zurück zum Zitat Paul, U., Ermakov, A., Nekrasov, M., Adarsh, V., Belding, E.: Outage: Detecting power and communication outages from social networks. In: Proceedings of The Web Conference 2020, WWW ’20, p. 1819–1829. Association for Computing Machinery, New York, NY, USA (2020). https://doi.org/10.1145/3366423.3380251 Paul, U., Ermakov, A., Nekrasov, M., Adarsh, V., Belding, E.: Outage: Detecting power and communication outages from social networks. In: Proceedings of The Web Conference 2020, WWW ’20, p. 1819–1829. Association for Computing Machinery, New York, NY, USA (2020). https://​doi.​org/​10.​1145/​3366423.​3380251
105.
110.
Zurück zum Zitat Ranneries, S.B., Kalør, M.E., Nielsen, S.A., Dalgaard, L.N., Christensen, L.D., Kanhabua, N.: Wisdom of the local crowd: Detecting local events using social media data. In: Proceedings of the 8th ACM Conference on Web Science, WebSci ’16, p. 352–354. Association for Computing Machinery, New York, NY, USA (2016). https://doi.org/10.1145/2908131.2908197 Ranneries, S.B., Kalør, M.E., Nielsen, S.A., Dalgaard, L.N., Christensen, L.D., Kanhabua, N.: Wisdom of the local crowd: Detecting local events using social media data. In: Proceedings of the 8th ACM Conference on Web Science, WebSci ’16, p. 352–354. Association for Computing Machinery, New York, NY, USA (2016). https://​doi.​org/​10.​1145/​2908131.​2908197
113.
Zurück zum Zitat Rudra, K., Ghosh, S., Ganguly, N., Goyal, P., Ghosh, S.: Extracting situational information from microblogs during disaster events: A classification-summarization approach. CIKM ’15, p. 583–592. Association for Computing Machinery, New York, NY, USA (2015). https://doi.org/10.1145/2806416.2806485 Rudra, K., Ghosh, S., Ganguly, N., Goyal, P., Ghosh, S.: Extracting situational information from microblogs during disaster events: A classification-summarization approach. CIKM ’15, p. 583–592. Association for Computing Machinery, New York, NY, USA (2015). https://​doi.​org/​10.​1145/​2806416.​2806485
117.
Zurück zum Zitat Schinas, M., Papadopoulos, S., Kompatsiaris, I., Mitkas, P.: Event detection and retrieval on social media. (2018) arXiv arXiv:1807.03675 Schinas, M., Papadopoulos, S., Kompatsiaris, I., Mitkas, P.: Event detection and retrieval on social media. (2018) arXiv arXiv:​1807.​03675
118.
Zurück zum Zitat Shao, M., Li, J., Chen, F., Huang, H., Zhang, S., Chen, X.: An efficient approach to event detection and forecasting in dynamic multivariate social media networks. In: Proceedings of the 26th International Conference on World Wide Web, WWW ’17, pp. 1631–1639. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE (2017). https://doi.org/10.1145/3038912.3052588 Shao, M., Li, J., Chen, F., Huang, H., Zhang, S., Chen, X.: An efficient approach to event detection and forecasting in dynamic multivariate social media networks. In: Proceedings of the 26th International Conference on World Wide Web, WWW ’17, pp. 1631–1639. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE (2017). https://​doi.​org/​10.​1145/​3038912.​3052588
120.
Zurück zum Zitat Shi, L.L., Wu, Y., Liu, L., Sun, X., Jiang, L.: Event detection and key posts discovering in social media data streams. In: 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), pp. 1046–1052 (2017). https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.159 Shi, L.L., Wu, Y., Liu, L., Sun, X., Jiang, L.: Event detection and key posts discovering in social media data streams. In: 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), pp. 1046–1052 (2017). https://​doi.​org/​10.​1109/​iThings-GreenCom-CPSCom-SmartData.​2017.​159
127.
Zurück zum Zitat Tung, K.C., Wang, E.T., Chen, A.L.P.: Mining event sequences from social media for election prediction. In: Perner, P. (ed.) Advances in Data Mining: Applications and Theoretical Aspects, pp. 266–281. Springer International Publishing, Cham (2016)CrossRef Tung, K.C., Wang, E.T., Chen, A.L.P.: Mining event sequences from social media for election prediction. In: Perner, P. (ed.) Advances in Data Mining: Applications and Theoretical Aspects, pp. 266–281. Springer International Publishing, Cham (2016)CrossRef
130.
Zurück zum Zitat Unankard, S., Nadee, W.: Sub-events tracking from social network based on the relationships between topics. In: 2020 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT NCON), pp. 1–6 (2020). https://doi.org/10.1109/ECTIDAMTNCON48261.2020.9090732 Unankard, S., Nadee, W.: Sub-events tracking from social network based on the relationships between topics. In: 2020 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT NCON), pp. 1–6 (2020). https://​doi.​org/​10.​1109/​ECTIDAMTNCON4826​1.​2020.​9090732
131.
Zurück zum Zitat Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. Adv. Neural Inf. Process. Syst. 30 (2017) Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. Adv. Neural Inf. Process. Syst. 30 (2017)
135.
Zurück zum Zitat Xing, C., Wang, Y., Liu, J., Huang, Y., Ma, W.: Hashtag-based sub-event discovery using mutually generative lda in twitter. In: AAAI (2016) Xing, C., Wang, Y., Liu, J., Huang, Y., Ma, W.: Hashtag-based sub-event discovery using mutually generative lda in twitter. In: AAAI (2016)
141.
Zurück zum Zitat Yan, X., Guo, J., Lan, Y., Xu, J., Cheng, X.: A probabilistic model for bursty topic discovery in microblogs. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, AAAI’15, pp. 353–359. AAAI Press (2015) Yan, X., Guo, J., Lan, Y., Xu, J., Cheng, X.: A probabilistic model for bursty topic discovery in microblogs. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, AAAI’15, pp. 353–359. AAAI Press (2015)
144.
Zurück zum Zitat Zhang, C., Zhou, G., Yuan, Q., Zhuang, H., Zheng, Y., Kaplan, L., Wang, S., Han, J.: Geoburst: Real-time local event detection in geo-tagged tweet streams. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’16, pp. 513–522. Association for Computing Machinery, New York, NY, USA (2016). https://doi.org/10.1145/2911451.2911519 Zhang, C., Zhou, G., Yuan, Q., Zhuang, H., Zheng, Y., Kaplan, L., Wang, S., Han, J.: Geoburst: Real-time local event detection in geo-tagged tweet streams. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’16, pp. 513–522. Association for Computing Machinery, New York, NY, USA (2016). https://​doi.​org/​10.​1145/​2911451.​2911519
146.
Zurück zum Zitat Zhao, Y., Jin, X., Wang, Y., Cheng, X.: Semi-supervised auto-encoder based event detection in constructing knowledge graph for social good. In: 2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pp. 478–485 (2019). https://doi.org/10.1145/3350546.3360736 Zhao, Y., Jin, X., Wang, Y., Cheng, X.: Semi-supervised auto-encoder based event detection in constructing knowledge graph for social good. In: 2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pp. 478–485 (2019). https://​doi.​org/​10.​1145/​3350546.​3360736
149.
Zurück zum Zitat Zhou, W., Shen, C., Li, T., Chen, S.C., Xie, N.: Generating textual storyline to improve situation awareness in disaster management. In: Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014), pp. 585–592 (2014). https://doi.org/10.1109/IRI.2014.7051942 Zhou, W., Shen, C., Li, T., Chen, S.C., Xie, N.: Generating textual storyline to improve situation awareness in disaster management. In: Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014), pp. 585–592 (2014). https://​doi.​org/​10.​1109/​IRI.​2014.​7051942
150.
Zurück zum Zitat Zhou, Y., De, S., Moessner, K.: Real world city event extraction from twitter data streams. Procedia Computer Science 98, 443–448 (2016). In: The 7th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2016)/The 6th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2016)/Affiliated Workshops https://doi.org/10.1016/j.procs.2016.09.069 Zhou, Y., De, S., Moessner, K.: Real world city event extraction from twitter data streams. Procedia Computer Science 98, 443–448 (2016). In: The 7th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2016)/The 6th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2016)/Affiliated Workshops https://​doi.​org/​10.​1016/​j.​procs.​2016.​09.​069
Metadaten
Titel
A survey on event and subevent detection from microblog data towards crisis management
verfasst von
Shatadru Roy Chowdhury
Srinka Basu
Ujjwal Maulik
Publikationsdatum
10.06.2022
Verlag
Springer International Publishing
Erschienen in
International Journal of Data Science and Analytics / Ausgabe 4/2022
Print ISSN: 2364-415X
Elektronische ISSN: 2364-4168
DOI
https://doi.org/10.1007/s41060-022-00335-y

Weitere Artikel der Ausgabe 4/2022

International Journal of Data Science and Analytics 4/2022 Zur Ausgabe

Premium Partner