PEMBANGUNAN MODEL PREDIKSI KEPRIBADIAN BERDASARKAN TWEET DAN KATEGORI KEPRIBADIAN BIG FIVE DENGAN METODE AGGLOMERATIVE HIERARCHICAL CLUSTERING

Authors

  • Axel Haikal Yusup Telkom University
  • Warih Maharani Telkom University

Abstract

Media sosial adalah forum tempat pengguna dapat berinteraksi dengan pengguna lain dan berbagi informasi melalui komunitas dan jejaring sosial. Banyaknya unggahan dari milyaran pengguna media sosial menjadi sumber data untuk mengekstrak dan membuat informasi baru. Penelitian dimulai dengan membagikan formulir kesediaan dan kuesioner untuk mendapatkan persetujuan dari responden yang menggunakan bahasa Indonesia di tweet mereka untuk berpartisipasi dalam penelitian ini. Agglomerative Hierarchical Clustering yang dipilih untuk memperkaya metode prediksi kepribadian seseorang berdasarkan konten di media sosial. Model pada penelitian ini memiliki akurasi 20.1% dengan rata-rata silhouette score -0.23. Keunikan kata yang tinggi dari setiap tweet yang diproses menjadi tantangan bagi model ini untuk menghasilkan performa yang optimal. Model ini dapat menangani data dalam jumlah besar dalam waktu singkat tetapi belum memberikan performa yang lebih optimal dibandingkan kasus serupa yang diselesaikan dengan supervised learning.

 

Kata kunci: media sosial, kepribadian, prediksi, metode, tweet

References

Alamsyah, A., Bastikarana, R.S., Ramadhanti, A.R. dan Widiyanesti, S., “Recognizing Personality from Social Media Linguistic Cues: A Case Study of Brand Ambassador Personality,” 2020 8th International Conference on Information and Communication Technology (ICoICT), pp. 1-5, Juni 2020.

Farnadi, G., Sitaraman, G., Sushmita, S., Celli, F., Kosinski, M., Stillwell, D., Davalos, S., Moens, M.F. and De Cock, M., “Computational personality recognition in social media,” User modeling and user-adapted interaction, 26(2-3), pp.109-142, 2016.

Kapoor, K.K., Tamilmani, K., Rana, N.P., Patil, P., Dwivedi, Y.K. dan Nerur, S., “Advances in social media research: Past, present and future,” Information Systems Frontiers, 20(3), pp.531-558, 2018.

Qiu, L., Lin, H., Ramsay, J. dan Yang, F., “You are what you tweet: Personality expression and perception on Twitter,” Journal of research in personality, 46(6), pp.710-718, 2012.

Rammstedt, B. dan John, O.P., “Measuring personality in one minute or less: A 10-item short version of the Big Five Inventory in English and German,” Journal of research in Personality, 41(1), pp.203-212, 2007.

Sahu, L. dan Mohan, B.R., “An improved K-means algorithm using modified cosine distance measure for document clustering using Mahout with Hadoop,” In 2014 9th International Conference on Industrial and Information Systems (ICIIS), pp. 1-5, 2014.

Sasirekha, K. dan Baby, P., “Agglomerative Hierarchical Clustering Algorithm-A Review,” International Journal of Scientific and Research Publications, pp.83, 2013

Ong, V., Rahmanto, A.D., Williem dan Suhartono, D., “Exploring personality prediction from text on social media: a literature review,” Internetworking Indonesia, 9(1): pp. 65-70, 2017.

Ahmad, N. dan Siddique, J., “Personality Assessment using Twitter Tweets,” Procedia Computer Science, pp. 1964-1973, 2017.

Goldberg, L.R., “An alternative “Description of personality”: The Big-Five Factor structure,” Personality and Personality Disorders: The Science of Mental Health, pp. 34, 2013.

Quercia, D., Michal, K., David, S. dan Jon, C., “Our twitter profiles, our selves: Predicting personality with twitter,” Proceedings - 2011 IEEE International Conference on Privacy, Security, Risk and Trust and IEEE International Conference on Social Computing, PASSAT/SocialCom 2011, pp. 180-185, 2011.

Jaimes Moreno, D. R., Carlos Gomez, J., Almanza-Ojeda, D. L. dan Ibarra-Manzano, M. A., “Prediction of personality traits in twitter users with latent features,” CONIELECOMP 2019 - 2019 International Conference on Electronics, Communications and Computers, Issue 3, pp. 176-181, 2019.

Ihsan, Z. dan Furnham, A., “The new technologies in personality assessment: A review,” Consulting Psychology Journal, 70(2), pp. 147–166, 2018.

Jeremy, N. H., Prasetyo, C. dan Suhartono, D., “Identifying personality traits for Indonesian user from twitter dataset,” International Journal of Fuzzy Logic and Intelligent Systems, 19(4): pp.283-289, 2019.

Yusra, Fikry, M., Syarfianto, R., Mai Candra, R., Budianta, E., “Klasifikasi Kepribadian Big Five Pengguna Twitter dengan Metode Naïve Bayes,” In Seminar Nasional Teknologi Informasi Komunikasi dan Industri, pp. 317-321, 2018.

Mann, A.K, dan Kaur, N., “Review paper on clustering techniques,” Global Journal of Computer Science and Technology, 2013.

Saitta, S., Raphael, B., dan Smith, I.F., “A bounded index for cluster validity,” In International workshop on machine learning and data mining in pattern recognition, pp. 174-187, July 2007.

Alamsyah, A., Putra, M.R.D., Fadhilah, D.D., Nurwianti, F. dan Ningsih, E., “Ontology Modelling Approach for Personality Measurement Based on Social Media Activity,” In 2018 6th International Conference on Information and Communication Technology (ICoICT), pp. 507-513, May 2018.

Mairesse, F., Walker, M.A., Mehl, M.R. dan Moore, R.K., “Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text,” Journal of Artificial Intelligence Research, 30, pp. 457-500, 2007.

Adi, G.Y.N., Tandio, M.H., Ong, V. dan Suhartono, D., “Optimization for automatic personality recognition on Twitter in Bahasa Indonesia,” Procedia Computer Science, 135: pp. 473-480, 2018.

Celli, F. and Rossi, L., “The Role of Emotional Stability in Twitter Conversations,” In Proceedings of the Workshop on Semantic Analysis in Social Media, pp. 10-17, April 2012.

Wu, C.H., “An Empirical Study on the Transformation of Likert-scale data to numerical scores,” Applied Mathematical Sciences, 1(58), pp.2851-2862, 2007.

Jeremy, N. H., Prasetyo, C. dan Suhartono, D., “Identifying personality traits for Indonesian user from twitter dataset,” International Journal of Fuzzy Logic and

Intelligent Systems, 19(4): pp.283-289, 2019.

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Published

2021-12-03