Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Survey on Online Social Media Networks Facebook Forensics Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Analysis of Text Messages in Social Media to Investigate CyberPsycho Attack

Authors : Prashant Gupta, Manisha J. Nene

Published in: Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 1

Publisher: Springer International Publishing

Log in

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

search-config
loading …

Abstract

Social media proved to be a medium to document our daily lives. It is a virtual tool used by an individual or organizations for various communications and information exchanges. Data available on social media assists in solving crimes; like to identify people, locations, evidence gathering notifying public, community, soliciting crimes etc. It is desired to attain privacy & security on these platforms. Further, it is observed that the information exchange and forwards are persuasive messages. These messages are intended to attain economical, political, religious, regional gains. The study in this paper proposes a model to analysis persuasive messages on social media. The results of the analysis demonstrate that these messages are the potential contents which leads to cyberpsycho attacks. The work in this paper is a step towards a study of threat analysis which demonstrates the psychological health of society & cyberpsycho attacks.

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!

inform now

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!

inform now

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!

inform now
previous chapter Multi-agent Simulation Model for Sequence Generation for Specially Abled Learners
next chapter K-Means Clustering with Neural Networks for ATM Cash Repository Prediction
Literature
1.
Prashant, G., Nene, M.J.: CyberPsycho attacks: techniques, causes, effects and recommendations to end-users. Int. J. Comput. Appl. 156, 11 (2016)
2.
Cheng, R.: Persuasion strategies for computers as persuasive technologies. Department of Computer Science, University of Saskatchewan, Saskatoon (2003)
3.
Preotiuc-Pietro, D., et al.: Trendminer: an architecture for real time analysis of social media text. In: Proceedings of the Workshop on Real-Time Analysis and Mining of Social Streams (2012)
4.
Stieglitz, S., Dang-Xuan, L.: Social media and political communication: a social media analytics framework. Soc. Network Anal. Min 3(4), 1277–1291 (2013)CrossRef
5.
Godbole, N., Srinivasaiah, M., Skiena, S.: Large-scale sentiment analysis for news and blogs. ICWSM 7(21), 219–222 (2007)
6.
Levon, L., Kechagias, D., Skiena, S.: Lydia: a system for large-scale news analysis. In: International Symposium on String Processing and Information Retrieval. Springer, Heidelberg (2005)
7.
Olga, S.: Mining trends in texts on the web. In: Proceedings of the Doctoral Consortium of the 3rd Future Internet Symposium (2010)
8.
Tiago, R., et al.: uTrack: track yourself! monitoring information on online social media. In: Proceedings of the 22nd International Conference on World Wide Web. ACM (2013)
9.
Tim, A., et al.: Analysis and forecasting of trending topics in online media streams. In: Proceedings of the 21st ACM International Conference on Multimedia. ACM (2013)
10.
Jey Han, L., Collier, N., Baldwin T.: On-line trend analysis with topic models:\# twitter trends detection topic model online In: COLING 2012 (2012)
11.
Kathy, L., et al.: Twitter trending topic classification. In: 2011 IEEE 11th International Conference on Data Mining Workshops (ICDMW). IEEE (2011)
12.
Raju, E., Sravanthi, K.: Analysis of social networks using the techniques of web mining. Int. J. 2, 10 (2012)
13.
Kristina, L., et al.: Emotions, Demographics and Sociability in Twitter (2016)
14.
Dongjin, C., et al.: Tracing trending topics by analyzing the sentiment status of tweets. Comput. Sci. Info. Syst. 11(1), 157–169 (2014)CrossRef
15.
Gupta, P., Nene, M. J.: An approach to analyze cyberpsycho attacks enabled using persuasive messages. In: 1st International Conference on Smart Computing & Informatics. Springer (in press, 2017)
Metadata
Title
Analysis of Text Messages in Social Media to Investigate CyberPsycho Attack
Authors
Prashant Gupta
Manisha J. Nene
Copyright Year
2018
Book
Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 1

Print ISBN: 978-3-319-63672-6

Electronic ISBN: 978-3-319-63673-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-63673-3_70

Premium Partner

    Image Credits