Enhancing Library Services Through User Response Analysis Based on Twitter Data Using Aspect Based Sentiment Analysis (ABSA)
DOI:
https://doi.org/10.24252/v13i2a6Keywords:
Library service, User experience, Sentiment analysis, Aspect Based Sentiment Analysis (ABSA)Abstract
Social media has become an essential part of everyday communication, including within the library context. Twitter, in particular, provides an Application Programming Interface (API) that enables real-time and comprehensive text-mining analyses of users’ perceptions and experiences. This study examines efforts to enhance library service quality by identifying and interpreting user sentiments on Twitter in a more detailed manner, enabling libraries to formulate targeted and effective service improvement strategies. The research consists of several stages: a literature review on sentiment analysis, data collection from Twitter using API-based data crawling, and a series of pre-processing steps, including data cleaning, case folding, tokenization, numerization, stopword removal, and stemming. Data were analyzed using the Aspect-Based Sentiment Analysis (ABSA) method. The findings indicate that the Collection and Facilities aspects receive the highest levels of positive sentiment, while Accessibility and Service attract considerable negative sentiment, signaling priority areas for improvement. Based on these results, libraries may consider extending operational hours, improving digital access, updating collections, and renovating facilities. Additionally, strengthening staff competencies and interpersonal skills is crucial for improving service quality and increasing user satisfaction.
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References
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Jalilifard, A., Caridá, V. F., Mansano, A. F., Cristo, R. S., & Da Fonseca, F. P. C. (2021). Semantic Sensitive TF-IDF to Determine Word Relevance in Documents. 736, 327–337. https://doi.org/10.1007/978-981-33-6987-0_27
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Obenauf, S. E. (2021). Remote management of library staff: Challenges and practical solutions. The Journal of Academic Librarianship, 47(5), 102353. https://doi.org/10.1016/j.acalib.2021.102353
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Pomputius, A. (2020). Assistive Technology and Software to Support Accessibility. Medical Reference Services Quarterly, 39(2), 203–210. https://doi.org/10.1080/02763869.2020.1744380
Rafiq, M., Batool, S. H., Ali, A. F., & Ullah, M. (2021). University libraries response to COVID-19 pandemic: A developing country perspective. The Journal of Academic Librarianship, 47(1), 102280.
Rahayu, S. (2017). Mengenal perpustakaan perguruan tinggi lebih dekat. Buletin Perpustakaan Universitas Islam Indonesia, 103–110.
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Shaw, J. N., & De Sarkar, T. (2021). A cloud-based approach to library management solution for college libraries. Information Discovery and Delivery, 49(4), 308–318. https://doi.org/10.1108/IDD-10-2019-0076
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Tandel, S. S., Jamadar, A., & Dudugu, S. (2019). A survey on text mining techniques. 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS), 1022–1026.
Tiurkedzhy, N. (2023). Digital Accessibility of Ukrainian Libraries: Analysis of Websites. Visnyk of Kharkiv State Academy of Culture, 63, 105–112. https://doi.org/10.31516/2410-5333.063.07
Trupthi, M., Pabboju, S., & Narasimha, G. (2017). Sentiment analysis on twitter using streaming API. 2017 IEEE 7th International Advance Computing Conference (IACC), 915–919.
Vorontsova, Yu. V., & Agibalova, A. D. (2021). Problems of digital library management. E-Management, 4(2), 51–57. https://doi.org/10.26425/2658-3445-2021-4-2-51-57
Yuliani, D. (2019). ANALISIS KEBIJAKAN STANDARISASI PERPUSTAKAAN PERGURUAN TINGGI (Kajian Terhadap Undang-Undang No. 43 Tahun 2007 Tentang Perpustakaan Dan Peraturan Pemerintah No. 24 Tahun 2014 Tentang Pelaksanaan UU No. 43 Tahun 2007 Tentang Perpustakaan). Moderat: Jurnal Ilmiah Ilmu Pemerintahan, 1(4), Article 4. https://doi.org/10.25147/moderat.v1i4.2851
Alshanik, F., Apon, A., Herzog, A., Safro, I., & Sybrandt, J. (2020). Accelerating Text Mining Using Domain-Specific Stop Word Lists. 2020 IEEE International Conference on Big Data (Big Data), 2639–2648. 2020 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/BigData50022.2020.9378226
Amarasekara, K. M. R. K., & Marasinghe, M. M. I. K. (2020). User Satisfaction on library resources and services: Survey conducted in main library of the Open University of Sri Lanka. Journal of the University Librarians Association of Sri Lanka, 23(2), 27–46. https://doi.org/10.4038/jula.v23i2.8007
Aribowo, A. S., Basiron, H., Yusof, N. F. A., & Khomsah, S. (2021). Cross-domain sentiment analysis model on Indonesian YouTube comment. International Journal of Advances in Intelligent Informatics, 7(1), 12. https://doi.org/10.26555/ijain.v7i1.554
Dai, X., Dai, H., Rong, C., Yang, G., Xiao, F., & Xiao, B. (2022). Enhanced Semantic-Aware Multi-Keyword Ranked Search Scheme Over Encrypted Cloud Data. IEEE Transactions on Cloud Computing, 10(4), 2595–2612. https://doi.org/10.1109/TCC.2020.3047921
Deich, D. (2020). Library’s personnel resources development as an integral part of its successful activity. Вісник Книжкової Палати, 7, 19–24. https://doi.org/10.36273/2076-9555.2020.7(288).19-24
Diyasa, I. G. S. M., Mandenni, N. M. I. M., Fachrurrozi, M. I., Pradika, S. I., Manab, K. R. N., & Sasmita, N. R. (2021). Twitter Sentiment Analysis as an Evaluation and Service Base On Python Textblob. IOP Conference Series: Materials Science and Engineering, 1125(1), 012034. https://doi.org/10.1088/1757-899X/1125/1/012034
Ezell, J., Pionke, J. J., & Gunnoe, J. (2022). Accessible services in academic libraries: A content analysis of library accessibility webpages in the United States. Reference Services Review, 50(2), 222–236. https://doi.org/10.1108/RSR-10-2021-0055
Gao, X., & Qi, M. (2023). Pre-processing of Social Media Remarks for Forensics. 2023 19th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), 1–6. 2023 19th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). https://doi.org/10.1109/ICNC-FSKD59587.2023.10280980
Gogoi, A., & Baruah, N. (2022). A Lemmatizer for Low-resource Languages: WSD and Its Role in the Assamese Language. ACM Transactions on Asian and Low-Resource Language Information Processing, 21(4), 1–22. https://doi.org/10.1145/3502157
HaCohen-Kerner, Y., Miller, D., & Yigal, Y. (2020). The influence of preprocessing on text classification using a bag-of-words representation. PLOS ONE, 15(5), e0232525. https://doi.org/10.1371/journal.pone.0232525
Hambarde, A. B. (2023). Stock verification via new media. IP Indian Journal of Library Science and Information Technology, 8(1), 63–67. https://doi.org/10.18231/j.ijlsit.2023.010
Hickman, L., Thapa, S., Tay, L., Cao, M., & Srinivasan, P. (2022). Text preprocessing for text mining in organizational research: Review and recommendations. Organizational Research Methods, 25(1), 114–146.
Hidayatullah, A. F., & Ma’arif, M. R. (2017). Pre-processing Tasks in Indonesian Twitter Messages. Journal of Physics: Conference Series, 801(1), 012072. https://doi.org/10.1088/1742-6596/801/1/012072
Hough, C., & Pomputius, A. (2022). Making Space for Wellness: Grant-funded Projects to Support Visitor Wellbeing in the Library. Journal of Hospital Librarianship, 22(1), 29–39. https://doi.org/10.1080/15323269.2021.2019513
Hu, J., Wang, X., Zhang, Y., Zhang, D., Zhang, M., & Xue, J. (2020). Time Series Prediction Method Based on Variant LSTM Recurrent Neural Network. Neural Processing Letters, 52(2), 1485–1500. https://doi.org/10.1007/s11063-020-10319-3
Ifada, N., Syachrudin, I., Sophan, M. K., & Wahyuni, S. (2019). Enhancing the Performance of Library Book Recommendation System by Employing the Probabilistic-Keyword Model on a Collaborative Filtering Approach. Procedia Computer Science, 157, 345–352. https://doi.org/10.1016/j.procs.2019.08.176
Jalilifard, A., Caridá, V. F., Mansano, A. F., Cristo, R. S., & Da Fonseca, F. P. C. (2021). Semantic Sensitive TF-IDF to Determine Word Relevance in Documents. 736, 327–337. https://doi.org/10.1007/978-981-33-6987-0_27
Juna, M. F., & Hayaty, M. (2023). The observed preprocessing strategies for doing automatic text summarizing. Computer Science and Information Technologies, 4(2), Article 2. https://doi.org/10.11591/csit.v4i2.p119-126
Longmeier, M. M., & Foster, A. K. (2022). Accessibility and Disability Services for Libraries: A Survey of Large, Research-Intensive Institutions. Portal: Libraries and the Academy, 22(4), 823–853. https://doi.org/10.1353/pla.2022.0044
Ma, Z. (2021). Research on Twitter Data Crawling and Data Visualization Analysis Based on Python. In W. Cao, A. Ozcan, H. Xie, & B. Guan (Eds.), Computing and Data Science (pp. 351–362). Springer Nature. https://doi.org/10.1007/978-981-16-8885-0_28
Maulana, A. S. (2016). Pengaruh kualitas pelayanan dan harga terhadap kepuasan pelanggan PT. TOI. Jurnal Ekonomi Universitas Esa Unggul, 7(2), 78663.
Migdalski, A., & Moreau, E. (2021). A matter of timing: Analyzing and adjusting library hours to suit students. Journal of Access Services, 18(2), 91–100. https://doi.org/10.1080/15367967.2021.1911660
Mowlaei, M. E., Abadeh, M. S., & Keshavarz, H. (2020). Aspect-based sentiment analysis using adaptive aspect-based lexicons. Expert Systems with Applications, 148, 113234.
Obenauf, S. E. (2021). Remote management of library staff: Challenges and practical solutions. The Journal of Academic Librarianship, 47(5), 102353. https://doi.org/10.1016/j.acalib.2021.102353
Peng, L., Wei, W., Fan, W., Jin, S., & Liu, Y. (2022). Student Experience and Satisfaction in Academic Libraries: A Comparative Study among Three Universities in Wuhan. Buildings, 12(5), 682. https://doi.org/10.3390/buildings12050682
Permana, D. R. (2022). AN ANALYSIS OF SLANG EXPRESSION TRANSLATION IN MOVIE. Global Expert: Jurnal Bahasa Dan Sastra, 10(1), 8–16. https://doi.org/10.36982/jge.v10i1.2160
Pomputius, A. (2020). Assistive Technology and Software to Support Accessibility. Medical Reference Services Quarterly, 39(2), 203–210. https://doi.org/10.1080/02763869.2020.1744380
Rafiq, M., Batool, S. H., Ali, A. F., & Ullah, M. (2021). University libraries response to COVID-19 pandemic: A developing country perspective. The Journal of Academic Librarianship, 47(1), 102280.
Rahayu, S. (2017). Mengenal perpustakaan perguruan tinggi lebih dekat. Buletin Perpustakaan Universitas Islam Indonesia, 103–110.
Ravikumar, S., Boruah, B. B., & Gayang, F. L. (2023). Text Mining of Journal Article Titles: An LDA-Based Topic Modeling Approach. Journal of Information and Knowledge, 289–295. https://doi.org/10.17821/srels/2023/v60i5/170707
Rizaty, M. A. (2022). Pengguna Twitter di Indonesia Capai 18,45 Juta pada 2022. Data Indonesia. https://dataindonesia.id/internet/detail/pengguna-twitter-di-indonesia-capai-1845-juta-pada-2022
Ruytenbeek, N., Allaert, J., & Vanderhasselt, M.-A. (2023). Psychophysiological effects of evaluative language use on Twitter complaints and compliments. Internet Pragmatics. https://doi.org/10.1075/ip.00092.ruy
Shaw, J. N., & De Sarkar, T. (2021). A cloud-based approach to library management solution for college libraries. Information Discovery and Delivery, 49(4), 308–318. https://doi.org/10.1108/IDD-10-2019-0076
Smoliar, I., & Turovska, L. (2020). Transformation of library and information services in terms of remote service. Вісник Книжкової Палати, 3, 17–20. https://doi.org/10.36273/2076-9555.2020.3(284).17-20
Song, Z., & Dang, L. (2022). Library Personalized Service System Based on Computer Network Technology. Security and Communication Networks, 2022, 1–6. https://doi.org/10.1155/2022/2550820
Tandel, S. S., Jamadar, A., & Dudugu, S. (2019). A survey on text mining techniques. 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS), 1022–1026.
Tiurkedzhy, N. (2023). Digital Accessibility of Ukrainian Libraries: Analysis of Websites. Visnyk of Kharkiv State Academy of Culture, 63, 105–112. https://doi.org/10.31516/2410-5333.063.07
Trupthi, M., Pabboju, S., & Narasimha, G. (2017). Sentiment analysis on twitter using streaming API. 2017 IEEE 7th International Advance Computing Conference (IACC), 915–919.
Vorontsova, Yu. V., & Agibalova, A. D. (2021). Problems of digital library management. E-Management, 4(2), 51–57. https://doi.org/10.26425/2658-3445-2021-4-2-51-57
Yuliani, D. (2019). ANALISIS KEBIJAKAN STANDARISASI PERPUSTAKAAN PERGURUAN TINGGI (Kajian Terhadap Undang-Undang No. 43 Tahun 2007 Tentang Perpustakaan Dan Peraturan Pemerintah No. 24 Tahun 2014 Tentang Pelaksanaan UU No. 43 Tahun 2007 Tentang Perpustakaan). Moderat: Jurnal Ilmiah Ilmu Pemerintahan, 1(4), Article 4. https://doi.org/10.25147/moderat.v1i4.2851
Published
2025-11-16
How to Cite
Rusydiyah, E. F., & Ananto, P. K. F. (2025). Enhancing Library Services Through User Response Analysis Based on Twitter Data Using Aspect Based Sentiment Analysis (ABSA). Khizanah Al-Hikmah : Jurnal Ilmu Perpustakaan, Informasi, Dan Kearsipan, 13(2). https://doi.org/10.24252/v13i2a6
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