Exploring the Effectiveness of Work from Home: A Text Mining Analysis of Employee Perceptions and Experiences

Reny Nadlifatin, Satria Fadil Persada*, Amanda Beatrice, Nadya Permata Putri, Michael Nayat Young, Yogi Tri Prasetyo*, Anak Agung Ngurah Perwira Redi

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Work from home (WFH) has become a global phenomenon that continues to grow, especially since the COVID-19 pandemic hit the world. Many organizations and companies are forced to adopt a remote working model to keep their employees safe. The usefulness of WFH is still up for dispute, though. Text mining analysis can be utilized to determine how beneficial working from home is. Sentiment analysis uses text analysis to gather ten thousand data from social media Tweets. Joy emotion is predicted to dominate with 83.98 percent according to the mining performed by the vocabulary valence aware dictionary and sentiment reasoner (VADER).

Original languageEnglish
Pages (from-to)448-454
Number of pages7
JournalProcedia Computer Science
Volume234
DOIs
Publication statusPublished - 2024
Event7th Information Systems International Conference, ISICO 2023 - Washington, United States
Duration: 26 Jul 202328 Jul 2023

Keywords

  • Sentiment
  • Text mining
  • Twitter
  • Work from home

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