Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Observing the Southern US Culture of Honor Using Large-Scale Social Media Analysis

Juho Kim, Michael Guerzhoy

Abstract

A \textit{culture of honor} refers to a social system where individuals' status, reputation, and esteem play a central role in governing interpersonal relations. Past works have associated this concept with the United States (US) South and related with it various traits such as higher sensitivity to insult, a higher value on reputation, and a tendency to react violently to insults. In this paper, we hypothesize and confirm that internet users from the US South, where a \textit{culture of honor} is more prevalent, are more likely to display a trait predicted by their belonging to a \textit{culture of honor}. Specifically, we test the hypothesis that US Southerners are more likely to retaliate to personal attacks by personally attacking back. We leverage OpenAI's GPT-3.5 API to both geolocate internet users and to automatically detect whether users are insulting each other. We validate the use of GPT-3.5 by measuring its performance on manually-labeled subsets of the data. Our work demonstrates the potential of formulating a hypothesis based on a conceptual framework, operationalizing it in a way that is amenable to large-scale LLM-aided analysis, manually validating the use of the LLM, and drawing a conclusion.

Observing the Southern US Culture of Honor Using Large-Scale Social Media Analysis

Abstract

A \textit{culture of honor} refers to a social system where individuals' status, reputation, and esteem play a central role in governing interpersonal relations. Past works have associated this concept with the United States (US) South and related with it various traits such as higher sensitivity to insult, a higher value on reputation, and a tendency to react violently to insults. In this paper, we hypothesize and confirm that internet users from the US South, where a \textit{culture of honor} is more prevalent, are more likely to display a trait predicted by their belonging to a \textit{culture of honor}. Specifically, we test the hypothesis that US Southerners are more likely to retaliate to personal attacks by personally attacking back. We leverage OpenAI's GPT-3.5 API to both geolocate internet users and to automatically detect whether users are insulting each other. We validate the use of GPT-3.5 by measuring its performance on manually-labeled subsets of the data. Our work demonstrates the potential of formulating a hypothesis based on a conceptual framework, operationalizing it in a way that is amenable to large-scale LLM-aided analysis, manually validating the use of the LLM, and drawing a conclusion.

Paper Structure

This paper contains 12 sections, 2 equations, 1 figure, 7 tables.

Table of Contents

  1. Introduction
  2. Related Works
  3. How a Culture of Honor Might Manifest on the Internet
  4. Methodology
  5. Analysis
  6. Discussion
  7. Conclusion
  8. Statistics on the Users with Identifiable US Region Information
  9. Information on the Fine-Tuned GPT-3.5 Models
  10. Aggression, Response, and Retaliation Rates
  11. R Code for Fitting a Mixed-Effect Model
  12. Statistics on the Ongoing Fights Detected by our System

Figures (1)

  • Figure 1: The bar graphs of all rates for the subreddit-changemyview dataset by metrics and US regions. The metric labels "AGG," "RESP," and "RET" represent aggression, response, and retaliation rates, respectively. Note that the retaliation rates corresponding to the US South are greater than or equal to those of the US non-South.