Abstract
With the wide adoption of social media, and the soaring volumes of brand-related social media conversations, manual approaches to content analysis are no longer practical.
Instead, automated computational methods are now required to efficiently analyse the large volume of content data. A recent trend is to classify content according to consumers’
feelings and opinions about brands by deploying content analysis techniques for sentiment classification. We argue existing techniques used in academic research and industry practice do not fit the type of data social media provides. This study compares the lexicon-based approach to sentiment analysis with computer supervised learning approach using Facebook data. Results show the two approaches are similar in accuracy but differ substantially in their classification ensembles. To rectify the differences, this study combines the two approaches and demonstrates improved outcomes.
Instead, automated computational methods are now required to efficiently analyse the large volume of content data. A recent trend is to classify content according to consumers’
feelings and opinions about brands by deploying content analysis techniques for sentiment classification. We argue existing techniques used in academic research and industry practice do not fit the type of data social media provides. This study compares the lexicon-based approach to sentiment analysis with computer supervised learning approach using Facebook data. Results show the two approaches are similar in accuracy but differ substantially in their classification ensembles. To rectify the differences, this study combines the two approaches and demonstrates improved outcomes.
| Original language | English |
|---|---|
| Title of host publication | ANZMAC 2016 |
| Subtitle of host publication | Marketing in a post-disciplinary era : proceedings |
| Editors | David Fortin, Lucie K. Ozanne |
| Place of Publication | Christchurch, NZ |
| Publisher | University of Canterbury |
| Pages | 300-307 |
| Number of pages | 8 |
| ISBN (Print) | 9780473376604 |
| Publication status | Published - 2016 |
| Event | Australia New Zealand Marketing Academy Conference - University of Canterbury, Christchurch, New Zealand Duration: 5 Dec 2016 → 7 Dec 2016 |
Conference
| Conference | Australia New Zealand Marketing Academy Conference |
|---|---|
| Abbreviated title | ANZMAC |
| Country/Territory | New Zealand |
| Period | 5/12/16 → 7/12/16 |
Keywords
- social media
- marketing analytics
- sentiment analysis
- big dat