Predicting Alcoholism Recovery from Twitter

By Jennifer Golbeck. 2018

8 citations recorded by the source corpus.

Subfields: Epidemiology, Social Psychology, Natural Language Processing, Social Sciences & Humanities

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Epidemiology

1. William S. Isaac
2. Iason Gabriel

In Social Psychology

1. Iason Gabriel
2. Geoffrey Irving
3. Zachary Kenton
4. Laura Weidinger
5. Abeba Birhane

In Natural Language Processing

1. Iason Gabriel
2. John F. J. Mellor
3. Borja Balle
4. Geoffrey Irving
5. Amelia Glaese
6. Myra Cheng
7. Lisa Anne Hendricks
8. Po-Sen Huang

In Social Sciences & Humanities

1. William S. Isaac
2. Iason Gabriel
3. Atoosa Kasirzadeh
4. Abeba Birhane

Citations in the corpus

• Ethical and social risks of harm from Language Models (2021, background): “Language utterances (e.g. tweets) are already being analysed to predict private information such as political orientation (Makazhanov et al., 2014; Preoţiuc-Pietro et al., 2017), age (Morgan-Lopez et al., 2017; Nguyen et al., 2013), and health data such as addiction relapses (Golbeck, 2018).”
• Taxonomy of Risks posed by Language Models (2022, background): “Tweets) are already being analysed to predict private information such as political orientation [121, 144], age [131, 135], and health data such as addiction relapses [63].”