Kaelyn Lamp

Kaelyn Lamp

Computational Psycholinguist

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

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This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

publications

talks

The Linguistic Expression of Hate Speech: A Corpus Analysis of Causal Constructions in Hate Speech

Published:

Limited work quantitatively analyzes how linguistic phenomena are used to manipulate the perception of causality and blame when expressing hate speech. Using annotated hate speech datasets, we conducted a corpus analysis of select causal constructions and strategies of indirect speech to see what syntactic choices were made by writers of hate speech when referencing minority (targeted) groups and majority groups. We found that hate speech tends to use causal constructions to minimize the causal responsibility of majority groups and indirect speech strategies such as word order and passivization to focus on the minority group’s involvement in events. Poster

Causality in Hate Speech

Published:

Limited work quantitatively analyzes how linguistic phenomena are used to manipulate the perception of causality and blame when expressing hate speech. Using annotated hate speech datasets, we conducted a corpus analysis of select causal constructions and strategies of indirect speech to see what syntactic choices were made by writers of hate speech when referencing minority (targeted) groups and majority groups. We found that hate speech tends to use causal constructions to minimize the causal responsibility of majority groups and indirect speech strategies such as word order and passivization to focus on the minority group’s involvement in events.

A Linguistic Analysis of Causality in Hate Speech

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This dissertation investigates how linguistic phenomena are used to manipulate the perception of causal responsibility and blame when expressing hate speech. The research questions addressed are as follows: (1) How is responsibility being assigned? (2) Are different types of causal constructions and strategies used similarly in hate speech? (3) Do the strategies vary based on language or are they universal? (4) How significant is causal responsibility in hate speech? To answer research questions (1) and (2), we conducted a corpus analysis of select causal constructions and strategies of indirect speech using annotated English hate speech datasets to see what syntactic choices were made by writers of hate speech when referencing minority (targeted) groups and majority groups. We found that hate speech tends to use causal constructions to minimize the causal responsibility of majority groups and indirect speech strategies such as word order and passivization to focus on the minority group’s involvement in events. To answer research question (3), we extended the corpus study to include English, Spanish, German, and French. The same causal constructions and strategies of indirect speech were analyzed. We found that the strategies used to manipulate the assignment of causal responsibility do vary cross-linguistically. For example, passive voice and causative verbs were used more frequently in English hate speech and implicit causality verbs were used more in Spanish and German hate speech. None of the syntactic choices examined were used to assign less causal responsibility to minority groups than majority groups in hate speech. Finally, to answer research question (4), we trained models to detect hate speech using causal information to test how predictive and generalizable the patterns regarding the assignment of causal responsibility in hate speech are. We found that the models did learn patterns related to the assignment of causal responsibility and that those patterns generalize better than patterns related to lexical choice.

teaching