How Social Media Reacting to Bakso Malang as Culinary Business on Post Covid 19: A Sentiment Analysis
Year: 2024
Type: conference-paper
Abstract: Indonesian cuisine, especially Bakso, is one of the trendy foods that many travelers try to consume. Among the variations of Bakso, Bakso Malang is one of the most popular variants that is much talked about in social media. The present study analyzes the sentiment text mining of Bakso Malang business on post covid period from a natural language processing (NLP) social perspective. The data was taken from scraping to social media by “bakso malang” keywords. A total of 331 lexicon-filtering Tweets were gathered in the middle of March 2023. The corpus data were analyzed by valance aware dictionary and sentiment reasoner (Vader) sentiment analysis. K-means conducted the cluster of expressions. The result shows the variation of sentiments expressed in social media by anger, disgust, fear, joy, sadness, and surprise with 1.21%, 1.21%, 4.83%, 32.33%, 3.02%, and 57.40%, respectively. Many contents were discussed with keywords of “malang”, “bakso”, “enak”, “makan”, “foodfess2”, “mau”, and “pengen”. Behavioural insight shows joy expression when discussing Bakso Malang. Further insights and recommendations are discussed in the paper.
Source: Procedia Computer Science
Authors: Satria Fadil Persada, Riesta Devi Kumalasari, Mardhatilah Shanti, Kukuh Lukiyanto, Gabriella Sagita Putri, Chelsea Aisiyah Ramadhan, Michael Nayat Young, Yogi Tri Prasetyo
Institutions: Binus University, Mapúa University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4396220497