Skip to main content
SpringerLink
Log in

Analyzing User Behavior and Sentimental in Computer Mediated Communication

  • Conference paper
  • First Online:
Image Processing and Capsule Networks (ICIPCN 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1200))

Included in the following conference series:

  • 832 Accesses

Abstract

Social media platforms are witnessing significant growth in both size and purpose. One specific aspect of social media platforms is sentiment analysis, by which insights into the emotions and feelings of a person can be inferred from their posted text. Twitter is a widely known social media platform in which users from different cultural and linguistic backgrounds. It is also valuable in studying a large amount of data and turning it into valuable information that can be useful in decision making. This study aims at investigating the sentiment orientation of the textual features as well as the emojis-based features of Arabic comments posted on social media, Twitter, during the World Cup 18 event. It also measures whether different results will be obtained when the text is analyzed in isolation from emojis. This paper presents the approach that involves extracting thousands of tweets, implementing the sentiment analysis, on the texts, and the emojis separately. This analysis has been conducted once via a using an artifact and once again manually, then a comparison between the results is made. This comparison shows that emojis support the sentiment orientation in the text. However, it can be relied solely neither on the text nor on emojis as they complement each other.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Cook, C.: Mobile marketing and political activities. Int. J. Mob. Mark. 5(1) (2010)

    Google Scholar 

  2. Leung, L.: Predicting internet risks: a longitudinal panel study of gratifications-sought, internet addiction symptoms, and social media use among children and adolescents. Health Psychol. Behav. Med. J. 2(1), 424–439 (2014). https://doi.org/10.1080/21642850.2014.902316

    Article  Google Scholar 

  3. Liu, B.: Sentiment analysis and opinion mining. Synth. Lect. Hum. Lang. Technol. 5(1), 1–167 (2012)

    Article  Google Scholar 

  4. Phillips, C.: Millennials Tech-Dependent, But Not Necessarily Tech-Savvy. Millennial Marketing Insights. http://millennialmarketing.com/2010/04/millennials-tech-dependent-but-not-necessarily-tech-savvy/

  5. Han, J., Pei, J., Kamber, M.: Data Mining: Concepts and Techniques. Elsevier, Amsterdam (2011)

    MATH  Google Scholar 

  6. Hakami, S. A. A.: The importance of understanding Emoji: an investigative study. In: Research Topics in HCI, pp. 1–20 (2017)

    Google Scholar 

  7. Miller, H., Thebault-Spieker, J., Chang, S., Johnson, I., Terveen, L., Hecht, B.: Blissfully “happy” or “ready to fight”: varying interpretations of Emoji. In: Proceedings of ICWSM (2016)

    Google Scholar 

  8. Seyednezhad, S.M., Menezes, R.: Understanding subject-based emoji usage using network science. In: Workshop on Complex Networks CompleNet, pp. 151–159. Springer, Cham, March 2017

    Google Scholar 

  9. Mjhool, A.Y.: Evaluation of user perceived QoE in mobile systems using social media analytics. Doctoral dissertation (2016)

    Google Scholar 

  10. Bumgarner, B. A.: You have been poked: exploring the uses and gratifications of Facebook among emerging adults. First Monday 12(11) (2007). https://doi.org/10.5210/fm.v12i11.2026

  11. Sheldon, P.: The relationship between unwillingness-to-communicate and students’ Facebook use. J. Media Psychol.: Theories Methods Appl. 20(2), 67 (2008). https://doi.org/10.1027/1864-1105.20.2.67

    Article  Google Scholar 

  12. Urista, M.A., Dong, Q., Day, K.D.: Explaining why young adults use MySpace and Facebook through uses and gratifications theory. Hum. Commun. 12(2), 215–229 (2009)

    Google Scholar 

  13. Hew, K.F., Cheung, W.S.: Use of Facebook: a case study of Singapore students’ experience. Asia Pac. J. Educ. 32(2), 181–196 (2012). https://doi.org/10.1080/02188791.2012.685560

    Article  Google Scholar 

  14. Pai, P., Arnott, D.C.: User adoption of social networking sites: eliciting uses and gratifications through a means-end approach. Comput. Hum. Behav. 29(3), 1039–1053 (2013). https://doi.org/10.1016/j.chb.2012.06.025

    Article  Google Scholar 

  15. Alhabash, S., Chiang, Y.H., Huang, K.: MAM & U&G in Taiwan: differences in the uses and gratifications of Facebook as a function of motivational reactivity. Comput. Hum. Behav. 35, 423–430 (2014). https://doi.org/10.1016/j.chb.2014.03.033

    Article  Google Scholar 

  16. Salem, F., Mourtada, R.: Social media in the Arab world: influencing societal and cultural change. Arab Soc. Media Rep. 2(1), 1–29 (2012)

    Google Scholar 

  17. Solberg, C.A.: Culture and industrial buyer behavior: the Arab experience. In: 18th IMP Conference (2002). http://impgroup.org/uploads/papers/522.pdf

  18. Miladi, N.: New media and the Arab revolution: citizen reporters and social activism. J. Arab Muslim Media Res. 4(2/3), 3–5 (2011). http://www.intellectbooks.co.uk/journals/view-jour

  19. Aljasir, S., Bajnaid, A., Elyas, T., Alnawasrah, M.: University students usage of Facebook: the case of obtained gratifications and typology of its users. J. Manag. Strategy 8(5), 30 (2017). https://doi.org/10.5430/jms.v8n5p30

    Article  Google Scholar 

  20. Arab Social Media Report: A Report on Facebook Usage: Factors and Analysis, vol. 1, no. 1 (2011). http://unpan1.un.org/intradoc/groups/public/documents/dsg/unpan044212.pdf. Accessed 17 Sept 2016

  21. Ahmari, Ali bin Said, the purpose of the use of university students to social networking sites: a field study on students University of Imam Muhammad bin Saud Islamic University of Imam Muhammad bin Saud Islamic University, Unpublished MA Thesis, 1432 AH. https://doi.org/10.13189/ujp.2015.030302

  22. Alsanie, S.I.: Social media (Facebook, Twitter, WhatsApp) used, and it’s relationship with the university students contact with their families in Saudi Arabia. Universal Journal of Psychology 3(3), 69–72 (2015). https://doi.org/10.13189/ujp.2015.030302

    Article  Google Scholar 

  23. https://www.shamra.sy/academia/download_document/document_cf5588e58ae3cc4deb18d1d0c87130ab.pdf. http://www.statisticbrain.com/twitter-statistics.5.1.2014.s

  24. Davis, M., Edberg, P.: Unicode Emoji, November 2016. http://unicode.org/reports/tr51/

  25. Stark, L., Crawford, K.: The conservatism of Emoji: work, affect, and communication. Soc. Media + Soc. 1(2), 2056305115604853 (2015). https://doi.org/10.1177/2056305115604853

  26. Taboada, M., Brooke, J., Tofiloski, M., Voll, K., Stede, M.: Lexicon-based methods for sentiment analysis. Comput. Linguist. 37(2), 267–307 (2011). https://doi.org/10.1162/COLI_a_00049

    Article  Google Scholar 

  27. Preisendorfer, M., Sengupta, S., White, J., Tekeoglu, A.: Social media Emoji analysis, correlations and trust modeling. Doctoral dissertation (2018). http://hdl.handle.net/1951/69574

  28. Alsanie, S.I.: Social media (Facebook, Twitter, WhatsApp) used, and it’s relationship with the university students contact with their families in Saudi Arabia. Univ. J. Psychol. 3(3), 69–72 (2015). https://doi.org/10.13189/ujp.2015.030302

    Article  Google Scholar 

  29. Abdulla, N.A., Ahmed, N.A., Shehab, M.A., Al-Ayyoub, M., Al-Kabi, M.N., Al-rifai, S.: Towards improving the lexicon-based approach for arabic sentiment analysis. Int. J. Inf. Technol. Web Eng. (IJITWE) 9(3), 55–71 (2014). https://doi.org/10.4018/ijitwe.2014070104

    Article  Google Scholar 

  30. Alshenqeeti, H.: Are emojis creating a new or old visual language for new generations? A socio-semiotic study. Adv. Lang. Literary Stud. 7(6), 56–69 (2016). http://journals.aiac.org.au/index.php/alls/article/view/2823

  31. Hajjous, M.: Opinions analysis in Tweeter. J. Alba’ath Univ. 38(41), 31–63 (2016)

    Google Scholar 

  32. He, Y., Zhou, D.: Self-training from labelled features for sentiment analysis. Inf. Process. Manag. 47(4), 606–616 (2011). https://doi.org/10.1016/j.ipm.2010.11.003

  33. Read, J., Carroll, J.: Weakly supervised techniques for domain-independent sentiment classification. In: The 1st International CIKM Workshop on Topic-Sentiment Analysis for Mass Opinion, pp. 45–52. ACM (2009). https://doi.org/10.1145/1651461.1651470

  34. Aleqabie, H.J., Safoq, M.S., Raoof, I., Alsabah, R., Abd, E.H.: Sentiment analysis for movie reviews using deep learning with semantic orientation. In: 8th International Conference on Applied Science and Technology, ICAST 2020, April 2020

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Law College, Al-Nahrain University, Baghdad, Iraq

    Abdulrahman Alrumaih

  2. College of Science, Computer Science Department, University of Kerbala, Kerbala, Iraq

    Ruaa Alsabah & Hiba J. Aleqabie

  3. Information Technology Research Development Center, University of Kufa, Najaf, Iraq

    Ahmed Yaseen Mjhool

  4. Computer Engineering Department, Al-Taff College University, Kerbala, Iraq

    Ali Al-Sabbagh

  5. Ministry of Communication, ITPC, Babylon, Iraq

    Ali Al-Sabbagh

  6. Sheffield Hallam University, Sheffield, UK

    Abdulrahman Alrumaih & James Baldwin

Authors
  1. Abdulrahman Alrumaih
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ruaa Alsabah
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hiba J. Aleqabie
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ahmed Yaseen Mjhool
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ali Al-Sabbagh
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. James Baldwin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ali Al-Sabbagh .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Dayeh University, Changhua, Taiwan

    Joy Iong-Zong Chen

  2. Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial, Departamento de Engenharia Mecânica, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

  3. Department of Electronics and Computer Engineering, Tribhuvan University, Lalitpur, Nepal

    Subarna Shakya

  4. College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia

    Abdullah M. Iliyasu

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Alrumaih, A., Alsabah, R., Aleqabie, H.J., Mjhool, A.Y., Al-Sabbagh, A., Baldwin, J. (2021). Analyzing User Behavior and Sentimental in Computer Mediated Communication. In: Chen, J.IZ., Tavares, J.M.R.S., Shakya, S., Iliyasu, A.M. (eds) Image Processing and Capsule Networks. ICIPCN 2020. Advances in Intelligent Systems and Computing, vol 1200. Springer, Cham. https://doi.org/10.1007/978-3-030-51859-2_26

Download citation

Publish with us

Policies and ethics

Search

Navigation