# The False positive problem of automatic bot detection in social science research

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/the-false-positive-problem-of-automatic-bot-detection-in-social-science-research/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Adrian Rauchfleisch,Jonas Kaiser |
| Citations | 180 |
| DOI | 10.1371/journal.pone.0241045 |
| Fields | Computer Science,Social Sciences |
| Open Access | true |
| OA Status | gold |
| OA URL | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0241045&type=printable |
| OpenAlex ID | https://openalex.org/W3014935876 |
| PMID | 33091067 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Adrian Rauchfleisch](https://scholariq.org/researchers/adrian-rauchfleisch/)

## Paper journal

- [PLoS ONE](https://scholariq.org/journals/plos-one/)

## Paper primary topic

- [Spam and Phishing Detection](https://scholariq.org/topics/spam-and-phishing-detection/)

## Paper topics

- [Spam and Phishing Detection](https://scholariq.org/topics/spam-and-phishing-detection/)
- [Misinformation and Its Impacts](https://scholariq.org/topics/misinformation-and-its-impacts/)
- [Sentiment Analysis and Opinion Mining](https://scholariq.org/topics/sentiment-analysis-and-opinion-mining/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.