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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.00455 |
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| _version_ | 1866916307534872576 |
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| author | Stanier, Tessa Shin, Hagyeong |
| author_facet | Stanier, Tessa Shin, Hagyeong |
| contents | This study investigates whether division on political topics is mapped with the distinctive patterns of language use. We collect a total 145,832 Reddit comments on the abortion debate and explore the languages of subreddit communities r/prolife and r/prochoice. With consideration of the Moral Foundations Theory, we examine lexical patterns in three ways. First, we compute proportional frequencies of lexical items from the Moral Foundations Dictionary in order to make inferences about each group's moral considerations when forming arguments for and against abortion. We then create n-gram models to reveal frequent collocations from each stance group and better understand how commonly used words are patterned in their linguistic context and in relation to morality values. Finally, we use Latent Dirichlet Allocation to identify underlying topical structures in the corpus data. Results show that the use of morality words is mapped with the stances on abortion. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_00455 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Polarization and Morality: Lexical Analysis of Abortion Discourse on Reddit Stanier, Tessa Shin, Hagyeong Computation and Language Computers and Society This study investigates whether division on political topics is mapped with the distinctive patterns of language use. We collect a total 145,832 Reddit comments on the abortion debate and explore the languages of subreddit communities r/prolife and r/prochoice. With consideration of the Moral Foundations Theory, we examine lexical patterns in three ways. First, we compute proportional frequencies of lexical items from the Moral Foundations Dictionary in order to make inferences about each group's moral considerations when forming arguments for and against abortion. We then create n-gram models to reveal frequent collocations from each stance group and better understand how commonly used words are patterned in their linguistic context and in relation to morality values. Finally, we use Latent Dirichlet Allocation to identify underlying topical structures in the corpus data. Results show that the use of morality words is mapped with the stances on abortion. |
| title | Polarization and Morality: Lexical Analysis of Abortion Discourse on Reddit |
| topic | Computation and Language Computers and Society |
| url | https://arxiv.org/abs/2407.00455 |