Mining Social Media Data to Discover Topics of Sustainability: The Case of Luxury Cosmetics Brands and Animal Testing

Abstract

Animal experiments have been considered necessary procedures for safety verification and effectiveness validation in developing the products that directly affect the human body, such as medicines or cosmetics (Baumans, 2010; Hajar, 2011). For ending animal testing, social media can be a useful and effective tool for those opposed to animal testing and has been shown to produce measurable results (Wilkinson, 2014). The current research regarding sustainability and animal testing hasn't sufficiently taken advantage of the large-scale data set available online. By applying data-mining-based social network analysis, this study used the French cosmetics company NARS as an example to examine how public awareness and reaction to animal experiments is spread on social media. To quantify and identify the online discussion of Instagram and Twitter users across time, we analyzed two networks of hashtags connected through user posts. To generate the nodes, we first crawled all posts containing #animaltesting within four months for Instagram, one week for Twitter. In both networks, nodes are hashtags created by users when they publish posts on certain events. The findings will be useful for cosmetics companies, lawmakers, and animal advocacy organizations in understanding the network and information flow on social media and, in turn, know what information should be posted on social media to engage social media users and build positive brand reputation.