Mining consumers' sentiments toward halal cosmetics: a text analytics approach
Ali Feizollah et al.
What the paper says
Although social media plays an important role in mining consumers' opinions, there is no previous research examining consumers' sentiments toward halal cosmetics, thus this study examined halal cosmetics tweets. A total of 8,932 halal cosmetics tweets were collected through a custom Python script. To conduct the analysis, a text mining approach was used. Using semantic networks, the study identifies major popular skincare, lipstick and halal nail polish brands. The findings are of great potential importance to companies producing halal cosmetics, as they can provide insights into promoting halal cosmetics brands online. Marketers can also design their advertising campaigns based on positive tweets of users of halal cosmetics. This work contributes to the debate on behaviours of different consumers on social media by examining the sentiments and opinions expressed by them. Additionally, the study expands the literature pertaining to consumers' sentiment towards shariah based products via social media instead of the normal survey.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.