Abstract
Advertising researchers and practitioners are increasingly using social media analytics (SMA), but focused overviews that explain how to use various SMA techniques are scarce. We focus on how researchers and practitioners can computationally analyze topics of conversation in social media posts, compare each to a human-coded topic analysis of a brand’s Twitter feed, and provide recommendations on how to assess and choose which computational methods to use. The computational methodologies that we survey in this article are text preprocessed summarization, phrase mining, topic modeling, supervised machine learning for text classification, and semantic topic tagging.
Original language | English (US) |
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Pages (from-to) | 47-59 |
Number of pages | 13 |
Journal | Journal of Interactive Advertising |
Volume | 20 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2 2020 |
Keywords
- Social media analytics
- computational advertising
- machine learning
- topic discovery
- topic modeling
ASJC Scopus subject areas
- Communication
- Marketing