Social Media Data Analytics in the Automotive Industry: A Study of the Interactive Impact of Marketing Strategies and User Ratings

Abstract

In the era of ubiquitous social media, car companies are navigating the challenges of user feedback on these platforms. This study investigates the influence of social media interactions on the market competitiveness and brand image of automotive firms. Using Python for web scraping, this study collected and analyzed user comments from Sina Weibo, focusing on both traditional fuel and new energy car companies. The comments were subjected to sentiment analysis using a sentiment dictionary, revealing users' emotional tendencies towards various car brands. The findings indicate notable differences in social media sentiment and brand positioning among different car companies. These insights are crucial for automotive companies to leverage social media feedback to enhance their products, services, and brand strategies.