Skip to main content
Top

2018 | OriginalPaper | Chapter

Connecting Social Media Data with Observed Hybrid Data for Environment Monitoring

Authors : Jinyan Chen, Sen Wang, Bela Stantic

Published in: Intelligent Distributed Computing XI

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Environmental monitoring has been regarded as one of effective solutions to protect our living places from potential risks. Traditional methods rely on periodically recording assessments of observed objects, which results in large amount of hybrid data sets. Additionally public opinions regarding certain topics can be extracted from social media and used as another source of descriptive data. In this work, we investigate how to connect and process the public opinions from social media with hybrid observation records. Particularly, we study Twitter posts from designated region with respect to specific topics, such as marine environmental activities. Sentiment analysis on tweets is performed to reflect public opinions on the environmental topics. Additionally two hybrid data sets have been considered. To process these data we use Hadoop cluster and utilize NoSql and relational databases to store data distributed across nodes in share nothing architecture. We compare the public sentiments in social media with scientific observations in real time and show that the “citizen science” enhanced with real time analytics can provide avenue to nominatively monitor natural environments. The approach presented in this paper provides an innovative method to monitor environment with the power of social media analysis and distributed computing.

Dont have a licence yet? Then find out more about our products and how to get one now:

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!

Literature
1.
go back to reference Bjorkelund, E., Burnett, T., Norvag, K.: A study of opinion mining and visualization of hotel reviews. In: Proceedings of the 14th International Conference on Information Integration and Web-based Applications and Services, pp. 229–238 Bjorkelund, E., Burnett, T., Norvag, K.: A study of opinion mining and visualization of hotel reviews. In: Proceedings of the 14th International Conference on Information Integration and Web-based Applications and Services, pp. 229–238
2.
go back to reference Brob, J.: Aspect-oriented sentiment analysis of customer reviews using distant supervision techniques. Ph.D. Thesis, Department of Mathematics and Computer Science, University of Berlin Brob, J.: Aspect-oriented sentiment analysis of customer reviews using distant supervision techniques. Ph.D. Thesis, Department of Mathematics and Computer Science, University of Berlin
3.
go back to reference Claster, W., Dinh, Q., Cooper, M.: Naive bayes and unsupervised artificial neural nets for caneun tourism social media data analysis. In: Nature and Biologically Inspired Computing, in Proceedings of the Second World Congress on Nature and Biologically Inspired Computing, pp. 158–163 Claster, W., Dinh, Q., Cooper, M.: Naive bayes and unsupervised artificial neural nets for caneun tourism social media data analysis. In: Nature and Biologically Inspired Computing, in Proceedings of the Second World Congress on Nature and Biologically Inspired Computing, pp. 158–163
4.
go back to reference Claster, W., Dinh, Q., Cooper, M.: Thailand-tourism and conflict modelling sentiment from twitter tweets using nave bayes and unsupervised artificial neural nets. In: Proceedings of the second International Conference on Computational Intelligence, Modelling and Simulation, pp. 89–94 Claster, W., Dinh, Q., Cooper, M.: Thailand-tourism and conflict modelling sentiment from twitter tweets using nave bayes and unsupervised artificial neural nets. In: Proceedings of the second International Conference on Computational Intelligence, Modelling and Simulation, pp. 89–94
5.
go back to reference Franciscus, N., Milosevic, Z., Stantic, B.: Influence of parallelism property of streaming engines on their performance. In: ADBIS (Short Papers and Workshops) Communications in Computer and Information Science, vol. 637, pp. 104–111. Springer (2016) Franciscus, N., Milosevic, Z., Stantic, B.: Influence of parallelism property of streaming engines on their performance. In: ADBIS (Short Papers and Workshops) Communications in Computer and Information Science, vol. 637, pp. 104–111. Springer (2016)
6.
go back to reference Hutto, C., Gilbert, E.: Vader: A parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the 8th International AAAI Conference on Weblogs and Social Media Hutto, C., Gilbert, E.: Vader: A parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the 8th International AAAI Conference on Weblogs and Social Media
7.
go back to reference Kasper, W., Vela, M.: Sentiment analysis for hotel reviews. In: Proceedings of the Computational Linguistics-Applications Conference, pp. 45–52 Kasper, W., Vela, M.: Sentiment analysis for hotel reviews. In: Proceedings of the Computational Linguistics-Applications Conference, pp. 45–52
8.
go back to reference Meo, P., Messina, F., Rosaci, D., Sarne, M.: Combining trust and skills evaluation to form e-learning classes in online social networks. Inf. Sci. 405, 107–122 (2017)CrossRef Meo, P., Messina, F., Rosaci, D., Sarne, M.: Combining trust and skills evaluation to form e-learning classes in online social networks. Inf. Sci. 405, 107–122 (2017)CrossRef
9.
go back to reference Ribeiro, F., Araujo, M., Goncalves, P., Goncalves, M.F.B.: A benchmark comparison of state-of-the-practice sentiment analysis methods (2015). arXiv151201818N Ribeiro, F., Araujo, M., Goncalves, P., Goncalves, M.F.B.: A benchmark comparison of state-of-the-practice sentiment analysis methods (2015). arXiv151201818N
10.
go back to reference Sharma, D., Kulshreshtha, A., P. PaygudeShahrivari, S.: Tourview: sentiment based analysis on tourist domain. Int. J. Comput. Sci. Inf. Technol. 6(3), 2318–2320 (2015) Sharma, D., Kulshreshtha, A., P. PaygudeShahrivari, S.: Tourview: sentiment based analysis on tourist domain. Int. J. Comput. Sci. Inf. Technol. 6(3), 2318–2320 (2015)
11.
go back to reference Shi, H., Li, X.: A sentiment analysis model for hotel reviews based on supervised learning. In: International Conference on Machine Learning and Cybernetics, ICMLC 2011, Guilin, China, July 10–13, 2011, Proceedings, pp. 950–954 (2011) Shi, H., Li, X.: A sentiment analysis model for hotel reviews based on supervised learning. In: International Conference on Machine Learning and Cybernetics, ICMLC 2011, Guilin, China, July 10–13, 2011, Proceedings, pp. 950–954 (2011)
12.
go back to reference Stantic, B., Pokornỳ, J.: Opportunities in big data management and processing. Front. Artif. Intell. Appl. 270, 15–26 (2014). IOS Press Stantic, B., Pokornỳ, J.: Opportunities in big data management and processing. Front. Artif. Intell. Appl. 270, 15–26 (2014). IOS Press
Metadata
Title
Connecting Social Media Data with Observed Hybrid Data for Environment Monitoring
Authors
Jinyan Chen
Sen Wang
Bela Stantic
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-66379-1_12

Premium Partner