Abstract
Increasingly, customers use social media and other Internet-based applications (e.g., review sites) to voice their opinions and to express their sentiments about brands. These reviews influence brand identity, either directly (by affecting consumer behavior) or indirectly (by generating positive or negative word-of-mouth through online social networks). We present an automated methodology that can be used to collect data from popular brand review sites and discussion boards. Customer feedback is then analyzed using best-practices of text mining and supervised sentiment analysis. Strategic implications of customer sentiments are discussed as we explore the role of sentiment analysis on modification of branding strategy.
| Original language | English |
|---|---|
| Pages (from-to) | 311-318 |
| Number of pages | 8 |
| Journal | Model Assisted Statistics and Applications |
| Volume | 13 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jan 1 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 12 Responsible Consumption and Production
Keywords
- Attribute-based sentiment analysis
- Brand attributes
- Brand management
- Predictive modeling
- Supervised sentiment analysis
- Text mining
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