# Put your money where your mouth is: Using deep learning to identify consumer tribes from word usage

arXiv: https://arxiv.org/abs/2105.13036 · HTML: https://mlsanity.com/paper/2105.13036/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 91 references that are in the map.
- First posted on arXiv 27 May 2021.

## Builds on (most cited first, 6 of 6)

- [LSTM: A Search Space Odyssey](https://mlsanity.com/paper/1503.04069/) (2015)
- [The Semantic Brand Score](https://mlsanity.com/paper/2105.05781/) (2021)
- [The impact of virtual mirroring on customer satisfaction](https://mlsanity.com/paper/2105.09571/) (2021)
- [Measuring the impact of spammers on e-mail and Twitter networks](https://mlsanity.com/paper/2105.10256/) (2021)
- [It is rotating leaders who build the swarm: social network determinants of growth for healthcare virtual communities of practice](https://mlsanity.com/paper/2105.12659/) (2021)
- [Assessing perceived organizational leadership styles through twitter text mining](https://mlsanity.com/paper/2105.11276/) (2021)

## Abstract (arXiv)

Internet and social media offer firms novel ways of managing their marketing strategy and gain competitive advantage. The groups of users expressing themselves on the Internet about a particular topic, product, or brand are frequently called a virtual tribe or E-tribe. However, there are no automatic tools for identifying and studying the characteristics of these virtual tribes. Towards this aim, this paper presents Tribefinder, a system to reveal Twitter users' tribal affiliations, by analyzing their tweets and language use. To show the potential of this instrument, we provide an example considering three specific tribal macro-categories: alternative realities, lifestyle, and recreation. In addition, we discuss the different characteristics of each identified tribe, in terms of use of language and social interaction metrics. Tribefinder illustrates the importance of adopting a new lens for studying virtual tribes, which is crucial for firms to properly design their marketing strategy, and for scholars to extend prior marketing research.