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Journal of E-Technology

Author Profiling in Arabic Tweets: An Approach based on Multi-Classification with Word and Character Features

Yutong Sun, Hui Ning, Kaisheng Chen, Leilei Kong, Yunpeng Yang, Jiexi Wang, Haoliang Qi
Harbin Engineering University, Harbin, China., Heilongjiang Institute of Technology, Harbin, China., East China Normal University, Shanghai, China

Abstract: This paper focuses on the author profiling task published in the FIRE 2019 (Forum for Information Retrieval Evaluation), which includes automatic identification of the age, gender, and language variety of Arabic tweets. We think the author profiling task as a multi-Classification problem. We have used word and character based on TFIDF features, learned the logistic regression classifier to predict the labels. In the final results, our proposed method shows a good performance in terms of age prediction, the accuracy rate is 0.6250. Additionally, we have obtained 0.5111 and 0.9604 accuracy for gender and language variety classifications respectively. In the experiment, We have used the different feature combination and adjusted the feature parameters to test the system. The combination of word and character features can improve the prediction accuracy and enhance the system performance significantly.

Keywords: Author Profiling, Logistic Regression, Word and Characters Ngram Author Profiling in Arabic Tweets: An Approach based on Multi-Classification with Word and Character Features

DOI:https://doi.org/10.6025/jet/2020/11/2/60-63

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References:

[1] Marquardt James., et al. (2014). Age and Gender Identification in Social Media. In: CEUR Workshop Proceedings, vol.1180, p 1129-1136.

[2] Micha, B Meina., Karolina Brodzi D ska., Bartosz Celmer., Maja Czoków., Martyna Patera., Jakub Pezacki., Mateusz Wilk. (2013). Ensemble-based Classification for Author Profiling Using Various Features -Notebook for PAN at CLEF 2013. In: CLEF 2013 Evaluation Labs and Workshop-Working Notes Papers. Valencia, Spain.

[3] Pastor López-Monroy, A., Manuel Montes-y-Gómez., Hugo Jair Escalante., Luis Villaseñor- Pineda., Esaú Villatoro-Tello. (2014). Using Intra-Profile Information for Author Profiling- Notebook for PAN at CLEF 2014. In: CLEF 2014 Evaluation Labs and Workshop- Working Notes Papers. Valencia, Spain.

[4] Sharmila Devi, V., Kannimuthu, S., Ravikumar, G., Anand Kumar, M. (2018). KCE_DAlab @MAPonSMS-FIRE2018: Effective Word and Character-based Features for Multilingual Author Profiling. In: Working Notes for MAPonSMS at FIRE’18 -Workshop Proceedings of the 10th International Forum for Information Retrieval Evaluation, p 213-222. Gujarat, India.

[5] Rangel, F., Rosso, P., Charfi, A., Zaghouani, W., Ghanem, B., Snchez-Junquera, J. (2019). Overview of the track on author profiling and deception detection in arabic. In: Mehta P., Rosso P., Majumder P., Mitra M. (Eds.) Working Notes of the Forum for Information Retrieval Evaluation (FIRE 2019). CEUR Workshop Proceedings. In: CEUR-WS.org, Kolkata, India, December 12-15.

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