Twitter Data Extraction for Food and Beverage Business Analytics
Muhammad Atqa Adzkia Zaldi, Opim Salim Sitompul, Erna Budhiarti Nababan, Andrian Reinaldo Crispin · 2024
An essential objective of this project is the collection and analysis of Twitter data having a particular emphasis on improving the food and beverage industry, particularly in the context of the Indonesian language. This study collects three distinct datasets, namely location data, tweet data, and profile data by utilizing the Twitter API and Pentaho Data Integration (PDI). The research provides meaningful insights into consumer preferences and trends in Indonesia's digital ecosystem by analyzing tweet patterns, hashtag trends, and food and beverage-related keywords using an interactive dashboard developed using Streamlit and DuckDB. The findings underscore the value of social media data for enterprises in making well-informed evaluations, creating focused marketing strategies, and enhancing product development. Furthermore, the research suggests potential areas for future exploration, like enhancing the process of selecting keywords, using analysis powered by artificial intelligence, and closely examining highly active accounts to optimize online effectiveness. Through the implementation of these identified patterns, food and beverage companies can improve their online presence and engage with customers more effectively.