# Words and Action: Modeling Linguistic Leadership in #BlackLivesMatter Communities

arXiv: https://arxiv.org/abs/2412.02637 · HTML: https://mlsanity.com/paper/2412.02637/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 19 of its 93 references that are in the map.
- First posted on arXiv 3 Dec 2024.

## Builds on (most cited first, 19 of 19)

- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [Datasheets for Datasets](https://mlsanity.com/paper/1803.09010/) (2018)
- [Learning Word Vectors for 157 Languages](https://mlsanity.com/paper/1802.06893/) (2018)
- [Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes](https://mlsanity.com/paper/1711.08412/) (2017)
- [Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change](https://mlsanity.com/paper/1605.09096/) (2016)
- [Analysing Lexical Semantic Change with Contextualised Word Representations](https://mlsanity.com/paper/2004.14118/) (2020)
- [Statistically Significant Detection of Linguistic Change](https://mlsanity.com/paper/1411.3315/) (2014)
- [Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change](https://mlsanity.com/paper/1606.02821/) (2016)
- [Survey of Computational Approaches to Lexical Semantic Change](https://mlsanity.com/paper/1811.06278/) (2018)
- [Temporal Analysis of Language through Neural Language Models](https://mlsanity.com/paper/1405.3515/) (2014)
- [Divergent discourse between protests and counter-protests: #BlackLivesMatter and #AllLivesMatter](https://mlsanity.com/paper/1606.06820/) (2016)
- [Substitution-based Semantic Change Detection using Contextual Embeddings](https://mlsanity.com/paper/2309.02403/) (2023)
- [Simple dynamic word embeddings for mapping perceptions in the public sphere](https://mlsanity.com/paper/1904.03352/) (2019)
- [Follow the Leader: Documents on the Leading Edge of Semantic Change Get More Citations](https://mlsanity.com/paper/1909.04189/) (2019)
- [Abolitionist Networks: Modeling Language Change in Nineteenth-Century Activist Newspapers](https://mlsanity.com/paper/2103.07538/) (2021)
- [CL-IMS @ DIACR-Ita: Volente o Nolente: BERT does not outperform SGNS on Semantic Change Detection](https://mlsanity.com/paper/2011.07247/) (2020)
- [Predicting Long-Term Citations from Short-Term Linguistic Influence](https://mlsanity.com/paper/2210.13628/) (2022)
- [Out of the Shadows: Analyzing Anonymous' Twitter Resurgence during the 2020 Black Lives Matter Protests](https://mlsanity.com/paper/2107.10554/) (2021)
- [Framing Social Movements on Social Media: Unpacking Diagnostic, Prognostic, and Motivational Strategies](https://mlsanity.com/paper/2406.13820/) (2024)

## Abstract (arXiv)

In this project, we describe a method of modeling semantic leadership across a set of communities associated with the #BlackLivesMatter movement, which has been informed by qualitative research on the structure of social media and Black Twitter in particular. We describe our bespoke approaches to time-binning, community clustering, and connecting communities over time, as well as our adaptation of state-of-the-art approaches to semantic change detection and semantic leadership induction. We find substantial evidence of the leadership role of BLM activists and progressives, as well as Black celebrities. We also find evidence of the sustained engagement of the conservative community with this discourse, suggesting an alternative explanation for how we arrived at the present moment, in which "anti-woke" and "anti-CRT" bills are being enacted nationwide.