| 1. |
- Devinney, Hannah, 1995-, et al.
(author)
-
Developing a multilingual corpus of wikipedia biographies
- 2023
-
In: International conference. Recent advances in natural language processing 2023, large language models for natural language processing. - Shoumen, Bulgaria : Incoma ltd.. - 9789544520922
-
Conference paper (peer-reviewed)abstract
- For many languages, Wikipedia is the mostaccessible source of biographical information. Studying how Wikipedia describes the lives ofpeople can provide insights into societal biases, as well as cultural differences more generally. We present a method for extracting datasetsof Wikipedia biographies. The accompanying codebase is adapted to English, Swedish, Russian, Chinese, and Farsi, and is extendable to other languages. We present an exploratory analysis of biographical topics and gendered patterns in four languages using topic modelling and embedding clustering. We find similarities across languages in the types of categories present, with the distribution of biographies concentrated in the language’s core regions. Masculine terms are over-represented and spread out over a wide variety of topics. Feminine terms are less frequent and linked to more constrained topics. Non-binary terms are nearly non-represented.
|
|
| 2. |
- Ryazanov, Igor, 1996-, et al.
(author)
-
How does the language of 'threat' vary across news domains? : a semi-supervised pipeline for understanding narrative components in news contexts
- 2023
-
In: SAIS 2023. - : Swedish Artificial Intelligence Society. - 9789180752749 ; , s. 94-99
-
Conference paper (peer-reviewed)abstract
- By identifying and characterising the narratives told in news media we can better understand political and societal processes. The problem is challenging from the perspective of natural language processing because it requires a combination of quantitative and qualitative methods. This paper reports on work in progress, which aims to build a human-in-the-loop pipeline for analysing how the variation of narrative themes across different domains, based on topic modelling and word embeddings. As an illustration, we study the language associated with the threat narrative in British news media.
|
|
| 3. |
- Ryazanov, Igor, 1996-, et al.
(author)
-
Thesis Proposal: Detecting Agency Attribution
- 2024
-
In: Proceedings of the 18th conference of the European chapter of the association for computational linguistics. - : Association for Computational Linguistics (ACL). - 9798891760905 ; , s. 208-214
-
Conference paper (peer-reviewed)abstract
- We explore computational methods for perceived agency attribution in natural language data. We consider ‘agency’ as the freedom and capacity to act, and the corresponding Natural Language Processing (NLP) task involves automatically detecting attributions of agency to entities in text. Our theoretical framework draws on semantic frame analysis, role labelling and related techniques. In initial experiments, we focus on the perceived agency of AI systems. To achieve this, we analyse a dataset of English-language news coverage of AI-related topics, published within one year surrounding the release of the Large Language Model-based service ChatGPT, a milestone in the general public’s awareness of AI. Building on this, we propose a schema to annotate a dataset for agency attribution and formulate additional research questions to answer by applying NLP models.
|
|
