Aleksandra Sorokovikova


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LLMs Simulate Big5 Personality Traits: Further Evidence
Aleksandra Sorokovikova | Sharwin Rezagholi | Natalia Fedorova | Ivan P. Yamshchikov
Proceedings of the 1st Workshop on Personalization of Generative AI Systems (PERSONALIZE 2024)

An empirical investigation into the simulation of the Big5 personality traits by large language models (LLMs), namely Llama-2, GPT-4, and Mixtral, is presented. We analyze the personality traits simulated by these models and their stability. This contributes to the broader understanding of the capabilities of LLMs to simulate personality traits and the respective implications for personalized human-computer interaction.

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Echo-chambers and Idea Labs: Communication Styles on Twitter
Aleksandra Sorokovikova | Michael Becker | Ivan P. Yamshchikov
Proceedings of the Second Workshop on Natural Language Processing for Political Sciences @ LREC-COLING 2024

This paper investigates the communication styles and structures of Twitter (X) communities within the vaccination context. While mainstream research primarily focuses on the echo-chamber phenomenon, wherein certain ideas are reinforced and participants are isolated from opposing opinions, this study reveals the presence of diverse communication styles across various communities. In addition to the communities exhibiting echo-chamber behavior, this research uncovers communities with distinct communication patterns. By shedding light on the nuanced nature of communication within social networks, this study emphasizes the significance of understanding the diversity of perspectives within online communities.