Classification Arabic Twitter User’s Insights Using Rough Set Theory

  • Ahmed Tamam Department of Information System , Faculty of computers and Artificial intelligence, Cairo, Egypt
  • Hatem Abdelkader Department of Information System , Faculty of computers and Artificial intelligence, Cairo, Egypt
  • Asmaa Haroun Department of Information System , Faculty of computers and Artificial intelligence, Cairo, Egypt
Keywords: Data mining techniques, sentiment analysis, Rough set theory, Classification social media

Abstract

Nowadays, people using social media from around the world to share their daily affairs. Arabic twitter for example is a platform where users read, reply, post which known ‘tweets’. Users trading their opinions on different trends that are not equal in important and differed based on their power and interest. Tweets can provide rich information to make decision. The main objective of this paper is to present a framework for making a valuable decision through analyzing social users' insights based on their proximity to a particular trend with highlights their power in this trend. Tweets are exceedingly unstructured that makes it difficult to analyze. Nevertheless, our proposed model differs from previous research in this field it gathered the use of supervised and unsupervised machine learning algorithms. The process of performing this work as follows: classifying users based on the degree of their closeness/interest utilizing Mendelow’s power/interest matrix, rough set theory to eliminate the features that may be found in user profiles to find minimal sets of data. The proposed model applied two attribute reduction algorithms on our dataset to determine the optimal number of reducts for improving decision making from the user replies. In addition to, unsupervised machine learning to group their replies into subcategories such as positive, negative, or neutral. The experimental evaluation shows that Johnson algorithm has reduced the user attributes by 71% than genetic algorithm that utilized in a classification model.

References

AL-Rubaiee H, Qiu R, Alomar K and Li D," Sentiment Analysis of Arabic Tweets in e-Learning," JOURNAL OF COMPUTER SCIENCE, 12 (11), pp.553-563, 2016.

A. H. Elsaid, R. K. Salem, H. M. Abdul-kader,"Automatic Framework for Requirement Analysis Phase," 2016.

G. BAI, L. LIU, BO SUN, J. FANG," A survey of user classification in social networks," IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCES (ICSESS),SEPT. 2015.

T. Hughes, T. Osman. ,G. Alwakid, "Challenges in Sentiment Analysis for Arabic Social Networks," pp. 89-100, November 2017.

S. H. SHAIKH, L. M. R. J. LOBO," Revealing insights for sales based on analysis of Twitter product reviews," INTERNATIONAL CONFERENCE ON GLOBAL TRENDS IN SIGNAL PROCESSING, INFORMATION COMPUTING AND COMMUNICATION (ICGTSPICC),DEC.2016.

P. VASHISTH, K. MEEHAN," Gender Classification using Twitter Text Data," 31ST IRISH SIGNALS AND SYSTEMS CONFERENCE (ISSC), JUNE.2020.

J. ANTONIO,J. MORZAN,H. ALATRISTA,T. HERNANDAZ, AND J. BIAN, "Clustering and topic modeling over tweets: A comparison over a health dataset," IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), NOV.2019.

H. AlSalman, "An Improved Approach for Sentiment Analysis of Arabic Tweets in Twitter Social Media," 3rd International Conference on Computer Applications & Information Security (ICCAIS),MARCH, 2020.

Dainwei Chi, "Research on the Application of K-Means Clustering Algorithm in Student Achievement, "IEEE International Conference on Consumer Electronics and Computer Engineering(ICCECE),2021.

H. Al-Rubaiee, K. Alomor," Clustering Students‘ Arabic Tweets using Different Schemes," In 2017 International Journal of Advanced Computer Science and Applications(IJACSA), Vol. 8, No. 4, 2017

M. Saad, W. Ashour, "Arabic Text Classification Using Decision Trees," pp. 75-79, 2010.

S. Larabi,N. Alalyani,S. Alotaibi, S. Ghouzali, and I. Abunadi, "Arabic Natural Language Processing and Machine Learning-Based Systems," vol. 7, pp. 7011-7020, 2019.

E. Umargono, J. Endro, V. Gunawan, "K-Means Clustering Optimization using the Elbow Method and Early Centroid Determination Based-on Mean And Median," the International Conferences on Information System and Technology (CONRIST 2019), pages 234-240, Sept.2020.

I. H. Witten, E. Frank, M. Hall, and C. J. Pal," Data Mining Practical machine learning tools and techniques," ,2016.

M. Al-Mhairat,R. Alabbadi, R. Shaban, and A. AlQudab, "Performance Evaluation of Clustering Algorithms,",May.2019.

P. NAGAMMA, H. R. PRUTHVI, K. K. NISHA, AND N H SHWETHA," An improved sentiment analysis of online movie reviews based on clustering for box-office prediction," INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION & AUTOMATION,MAY.2015.

Z. Pawlak, " Rough Sets," International Journal of computer and Information Sciences, Vol.11, No. 5, 1982.

M. Bekkali, I. Sahmoudi, and A. Lachkar," Enriching Arabic tweets representation based on web search engine and the rough set theory," International Conference on Advances in Social Networks Analysis and Mining (ASONAM),Aug.2015.

WANG, J. YANG, R. JENSEN, X. LIU, "Rough set feature selection and rule induction for prediction of malignancy degree in brain glioma", COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 83, PP.147-156, 2006

C. LIAN, H. LIU, AND Z. WAN, "An attribute Reduction Algorithm Based on Rough Set Theory and An Improved Genetic Algorithm", JOURNAL OF SOFTWARE, 9(9), PP. 2276-2282, 2014.

A. Elsaid,R. Salem, "A dynamic stakeholder Classification and Prioritization Based on Hybrid Rough-Fuzzy Method," Journal of Software Engineering, no. 11, p. 143–159, 2017.

A Rough Set Rosetta Toolkit for Data Analysis and its functionality. available in: http://www.lcb.uu.se/tools /rosette/accessed 26 October 2013.

Published
2022-01-21
How to Cite
Ahmed Tamam, Hatem Abdelkader, & Asmaa Haroun. (2022). Classification Arabic Twitter User’s Insights Using Rough Set Theory. International Journal of Sciences: Basic and Applied Research (IJSBAR), 61(1), 115-133. Retrieved from https://www.gssrr.org/index.php/JournalOfBasicAndApplied/article/view/13672
Section
Articles