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İşletmelerde çalışanlara yönelik duygu analizinin uygulanması: Potansiyel faydalar ve zorluklar

Year 2024, Volume: 17 Issue: 3, 462 - 488, 31.07.2024
https://doi.org/10.25287/ohuiibf.1407694

Abstract

Duygu analizi, insanlara ait metin, görüntü ve ses gibi kaynaklardan elde edilen verileri inceleyerek insan duygularını analiz etmeyi ifade eden bir kavramdır. Bu araştırmanın amacı, işletmelerde çalışanlara yönelik duygu analizinin nasıl uygulanabileceğini ele almak ve çalışan duygularını analiz etmenin getireceği potansiyel faydalar ve zorlukları açıklamaktır. Bu makale, literatür taraması yöntemini kullanarak işletme çalışanları bağlamında duygu analizi ile ilgili çalışmaları inceleyip değerlendirmek suretiyle duygu analizi çabalarının işletmelere sağlayacağı fayda ve zorlukların karşılaştırılmasını kolaylaştırmayı ve bu yolla literatüre katkıda bulunmayı hedeflemektedir. Araştırma sonucunda işletmelerde duygu analizini kullanmanın, çalışan bağlılığını artırma, işten ayrılma riskini azaltma, veriye dayalı karar alma, potansiyel sorunları büyümeden önleme ve olumlu örgüt kültürü oluşturma gibi pek çok fayda sağladığı görülmüştür. Ancak aynı zamanda duygu analizi araçlarının mizah, iğneleme, ironi, jargon gibi özellikli ifadeleri anlamada zorluklar yaşadığı, karmaşık cümlelerin ve büyük miktarda veriyi analiz etmenin bir takım güçlükler oluşturduğu sonucuna varılmıştır. Bu sebeple işletmelerin çalışan duygularını daha iyi anlayabilmek için duygu analizinden yararlanmaları önerilmekle birlikte verilerin etkili bir şekilde işlenmesi için yapay zeka teknolojilerinin hala gelişmeye ihtiyacı olduğu ve teknoloji gelişmeye devam ettikçe duygu analizi araçlarının çalışan duygularını anlamada daha başarılı hale geleceği düşünülmektedir.

References

  • Agüero-Torales, M. M., Cobo, M. J., Herrera-Viedma, E. & López-Herrera, A. G. (2019). A cloud-based tool for sentiment analysis in reviews about restaurants on tripAdvisor. Procedia Computer Science, 162, 392–399. http://dx.doi.org/10.1016/j.procs.2019.12.002
  • Alamsyah, A. & Ginting, D. M. (2018, August). Analyzing employee voice using real-time feedback. 4th International Conference on Science and Technology, Yogyakarta, Indonesia.
  • Apostolidis, C., Devine, A. & Jabbar, A. (2022). From chalk to clicks – The impact of (rapid) technology adoption on employee emotions in the higher education sector. Technological Forecasting and Social Change, 182, 1-15. https://doi.org/10.1016/j.techfore.2022.121860
  • Aqel, D. & Vadera, S. (2010, June). A framework for employee appraisals based on sentiment analysis. 1st International Conference on Intelligent Semantic Web-Services and Applications, Amman, Jordan.
  • Archer, L. (2021). How do employees really feel? The power of sentiment analysis. Retrieved from https://explorance.com/blog/how-do-employees-really-feel-the-power-of-sentiment-analysis/ 06.11.2023
  • Bahri, S., Adiwisastra, M. F., Alawiyah, T., Purnia, D. S. & Simpony, B. K. (2020). Sentiment analysis for decision support systems of employee. Journal of Physics: Conference Series, 1477, 1-5. https://doi.org/10.1088/1742-6596/1477/2/022014
  • Beltramin, A. (2023). 5 Employee sentiment analysis tools to ımprove employee engagement in 2023. Retrieved from https://www.morphcast.com/5-employee-sentiment-analysis-tools-to-improve-employee- engagement/ 06.11.2023
  • Berkeley, D. (2023). Sentiment analysis overview. Retrieved from https://intellihr.zendesk.com/hc/en- us/articles/360000031736-Sentiment-Analysis-Overview 07.11.2023
  • Bharti, O. & Malhotra, M. (2016). Sentiment analysis on twitter data. International Journal of Computer Science and Mobile Computing, 5(6), 601-609.
  • Boudreau, J. & Cascio, W. (2017). Human capital analytics: Why are we not there?. Journal of Organizational Effectiveness: People & Performance, 4(2), 119-126. https://doi.org/10.1108/JOEPP-03-2017-0021
  • Calvin, P. (2023). Is employee feedback analysis possible with sentiment Analysis. Retrieved from https://simplified.com/docs/p/is-employee-feedback-analysis-possible-with-sentiment-analysis-fd4ffb79- ad6f-4ffa-a8b2-c6d558e2c134 07.11.2023
  • Cambria, E., Schuller, B., Xia, Y. & Havasi, C. (2013). New avenues in opinion mining and sentiment analysis. IEEE Intelligent Systems, 28(2), 15–21. https://doi.org/10.1109/MIS.2013.30
  • Carter, L. (2023). Employee sentiment analysis: Why you should care and 4 ways to measure it. Retrieved from https://mostlovedworkplace.com/employee-sentiment-analysis-why-you-should-care-and-4-ways-to- measure-it/ 06.11.2023
  • Chan, C. F. & Eric, W. M. (2010, August). An abnormal sound detection and classification system for surveillance applications. 18th European Signal Processing Conference, Aalborg, Denmark.
  • Chandrasekaran, G., Antoanela, N., Andrei, G., Monica, C. & Hemanth, J. (2022). Visual sentiment analysis using deep learning models with social media data. Applied Sciences, 12, 1-23. https://doi.org/10.3390/app12031030
  • Chang, Y. C., Ku, C. H. & Chen, C. H. (2019). Social media analytics: Extracting and visualizing hilton hotel ratings and reviews from tripadvisor. International Journal of Information Management, 48, 263–279. http://dx.doi.org/10.1016/j.ijinfomgt.2017.11.001
  • Chatterjee, D. P., Mukherjee, A., Mukhopadhyay, S., Panday, M., Panigrahi, P. K. & Goswami, S. (2021). A survey on sentiment analysis. In A. E. Hassanien et al. (Eds.), Emerging Technologies in Data Mining and Information Security (pp. 259-271). Singapore: Springer.

THE APPLICATION OF EMPLOYEE SENTIMENT ANALYSIS IN ORGANIZATIONS: POTENTIAL BENEFITS AND CHALLENGES

Year 2024, Volume: 17 Issue: 3, 462 - 488, 31.07.2024
https://doi.org/10.25287/ohuiibf.1407694

Abstract

Sentiment analysis is a concept that refers to analysing human sentiments by examining data obtained from sources such as text, image and sound. The purpose of this research is to address how employee sentiments analysis can be applied in organizations and to explain the potential benefits and challenges of analysing employee sentiments. This article aims to facilitate the comparison of the benefits and challenges that emotion analysis efforts can provide to businesses by reviewing and evaluating studies on emotion analysis in the context of business employees using the literature review method and thus contributing to the literature. As a result of the research, it was seen that using sentiment analysis in businesses provides many benefits such as increasing employee loyalty, reducing the risk of turnover, data-based decision making, preventing potential problems before they grow and creating a positive organizational culture. However, it was also concluded that sentiment analysis tools have difficulties in understanding specific expressions such as humour, sarcasm, irony and jargon, and that complex sentences and analysing large amounts of data pose some difficulties. For this reason, it is recommended that businesses should use of to better understand employee sentiments, but it is thought that artificial intelligence technologies still need to be developed in order to process data effectively and as technology continues to develop, sentiment analysis tools will become more successful in understanding employee sentiments.

References

  • Agüero-Torales, M. M., Cobo, M. J., Herrera-Viedma, E. & López-Herrera, A. G. (2019). A cloud-based tool for sentiment analysis in reviews about restaurants on tripAdvisor. Procedia Computer Science, 162, 392–399. http://dx.doi.org/10.1016/j.procs.2019.12.002
  • Alamsyah, A. & Ginting, D. M. (2018, August). Analyzing employee voice using real-time feedback. 4th International Conference on Science and Technology, Yogyakarta, Indonesia.
  • Apostolidis, C., Devine, A. & Jabbar, A. (2022). From chalk to clicks – The impact of (rapid) technology adoption on employee emotions in the higher education sector. Technological Forecasting and Social Change, 182, 1-15. https://doi.org/10.1016/j.techfore.2022.121860
  • Aqel, D. & Vadera, S. (2010, June). A framework for employee appraisals based on sentiment analysis. 1st International Conference on Intelligent Semantic Web-Services and Applications, Amman, Jordan.
  • Archer, L. (2021). How do employees really feel? The power of sentiment analysis. Retrieved from https://explorance.com/blog/how-do-employees-really-feel-the-power-of-sentiment-analysis/ 06.11.2023
  • Bahri, S., Adiwisastra, M. F., Alawiyah, T., Purnia, D. S. & Simpony, B. K. (2020). Sentiment analysis for decision support systems of employee. Journal of Physics: Conference Series, 1477, 1-5. https://doi.org/10.1088/1742-6596/1477/2/022014
  • Beltramin, A. (2023). 5 Employee sentiment analysis tools to ımprove employee engagement in 2023. Retrieved from https://www.morphcast.com/5-employee-sentiment-analysis-tools-to-improve-employee- engagement/ 06.11.2023
  • Berkeley, D. (2023). Sentiment analysis overview. Retrieved from https://intellihr.zendesk.com/hc/en- us/articles/360000031736-Sentiment-Analysis-Overview 07.11.2023
  • Bharti, O. & Malhotra, M. (2016). Sentiment analysis on twitter data. International Journal of Computer Science and Mobile Computing, 5(6), 601-609.
  • Boudreau, J. & Cascio, W. (2017). Human capital analytics: Why are we not there?. Journal of Organizational Effectiveness: People & Performance, 4(2), 119-126. https://doi.org/10.1108/JOEPP-03-2017-0021
  • Calvin, P. (2023). Is employee feedback analysis possible with sentiment Analysis. Retrieved from https://simplified.com/docs/p/is-employee-feedback-analysis-possible-with-sentiment-analysis-fd4ffb79- ad6f-4ffa-a8b2-c6d558e2c134 07.11.2023
  • Cambria, E., Schuller, B., Xia, Y. & Havasi, C. (2013). New avenues in opinion mining and sentiment analysis. IEEE Intelligent Systems, 28(2), 15–21. https://doi.org/10.1109/MIS.2013.30
  • Carter, L. (2023). Employee sentiment analysis: Why you should care and 4 ways to measure it. Retrieved from https://mostlovedworkplace.com/employee-sentiment-analysis-why-you-should-care-and-4-ways-to- measure-it/ 06.11.2023
  • Chan, C. F. & Eric, W. M. (2010, August). An abnormal sound detection and classification system for surveillance applications. 18th European Signal Processing Conference, Aalborg, Denmark.
  • Chandrasekaran, G., Antoanela, N., Andrei, G., Monica, C. & Hemanth, J. (2022). Visual sentiment analysis using deep learning models with social media data. Applied Sciences, 12, 1-23. https://doi.org/10.3390/app12031030
  • Chang, Y. C., Ku, C. H. & Chen, C. H. (2019). Social media analytics: Extracting and visualizing hilton hotel ratings and reviews from tripadvisor. International Journal of Information Management, 48, 263–279. http://dx.doi.org/10.1016/j.ijinfomgt.2017.11.001
  • Chatterjee, D. P., Mukherjee, A., Mukhopadhyay, S., Panday, M., Panigrahi, P. K. & Goswami, S. (2021). A survey on sentiment analysis. In A. E. Hassanien et al. (Eds.), Emerging Technologies in Data Mining and Information Security (pp. 259-271). Singapore: Springer.
There are 17 citations in total.

Details

Primary Language Turkish
Subjects Human Resources and Industrial Relations (Other), Business Administration
Journal Section Articles
Authors

Engin Yurdasever 0000-0002-3853-2032

Publication Date July 31, 2024
Submission Date December 20, 2023
Acceptance Date June 24, 2024
Published in Issue Year 2024 Volume: 17 Issue: 3

Cite

APA Yurdasever, E. (2024). İşletmelerde çalışanlara yönelik duygu analizinin uygulanması: Potansiyel faydalar ve zorluklar. Ömer Halisdemir Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 17(3), 462-488. https://doi.org/10.25287/ohuiibf.1407694

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Ömer Halisdemir Universitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi (OHUIIBF) is licensed under the Creative Commons Attribution-Noncommercial-Pseudonymity License 4.0 international license.