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Report on Analyzing Connotation Frames in Evolving Wikipedia Biographies — LessWrong

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Report on Analyzing Connotation Frames in Evolving Wikipedia Biographies

30th Aug 2023

4 min read

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ConnotationLanguage Models (LLMs)Machine Learning (ML)Social & Cultural Dynamics

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Decoding Sentiment and Connotation in Digital Narratives

In today's digital era, where information dissemination is predominantly online, the study of sentiment and connotation within textual content has gained unprecedented significance. This research report introduces a novel approach to dissecting these complex dynamics, focusing specifically on the realm of Wikipedia biographies. The objective is to unravel the layers of sentiment and connotation within these biographical narratives and explore their evolution over different temporal periods. By employing a data-driven methodology, this research aimed to quantify shifts in sentiment and connotation, offering a deeper understanding of how individuals are portrayed, and the emotions associated with them. This investigation has particular relevance in a time where online narratives profoundly shape public perceptions, as well as tracing the evolution of sentiment in Wikipedia biography portrayals in parallel with real-world evolving sentiments in society.

Sentiment Analysis and Connotation Frames

Sentiment analysis has long been an essential tool in natural language processing, allowing researchers to uncover emotional tones and opinions embedded within textual contexts. However, this report introduces a novel enhancement recently introduced—connotation frames. These frames go beyond traditional sentiment analysis by capturing implied sentiments, presupposed value judgments, and effect evaluations present within linguistic expressions. This dynamic combination empowers researchers to decode textual content on a more nuanced level, transcending the boundaries of simple positive/negative polarity analysis. This augmentation is a pivotal step in bridging the gap between explicit sentiments and the multi-dimensional layers of meaning concealed within language.

Wikipedia Biographies as Mirrors of Societal Attitudes

The vast repository of information on Wikipedia provides a fertile ground for understanding how sentiment and connotation evolve over time. Biographies, in particular, serve as powerful tools for this investigation. They offer glimpses into the evolution of sentiment and connotation, capturing changing societal perceptions that echo broader cultural shifts. In an age where digital narratives wield significant influence over public opinion, analyzing sentiment and connotation within Wikipedia biographies becomes increasingly crucial. This research aims to uncover latent biases, trace societal trends, and highlight the pervasive influence of media narratives. By examining curated biographies, we aimed to unearth subtle shifts in individual depictions and the sentiments associated with them, establishing a framework capable of identifying evolving sentiments and validating these findings against established methodologies.

Related Work: Foundations and Advancements

The paper by Rashkin, Singh, and Choi ("Connotation Frames: A Data-Driven Investigation") introduces the concept of connotation frames, revolutionizing sentiment analysis. The authors propose a unified framework that encapsulates implied sentiments, value judgments, and effect evaluations within predicate-argument structures. Unlike traditional sentiment lexicons, which assess word polarity without considering semantic arguments, this framework provides a holistic understanding of sentiment dynamics. The authors leverage connotation frames to analyze historical online content, revealing how sentiment relationships between different entities evolve over time. This work not only advances sentiment analysis but also offers insights into the interaction between language, sentiment, and context.

The paper by Field et al. ("Controlled Analyses of Social Biases in Wikipedia Bios") presents a meticulous methodology for investigating biases in Wikipedia biographical articles based on gender and race. The authors construct controlled datasets to compare articles about different identity groups, identifying content gaps and systemic biases. This study contributes to discourse on systemic bias in Wikipedia and provides insights for improving representation. Furthermore, the study by Park et al. ("Multilingual Contextual Affective Analysis of LGBT People Portrayals in Wikipedia") delves into sentiment analysis and connotation frames in the context of Wikipedia biographies about LGBT individuals. The authors examine linguistic attributes of sentiment, power, and agency, considering cross-cultural differences in portrayal. The study enhances analytical toolkits for examining biases and portrayal in online narratives.

Methodology: Sentiment and Connotation Dynamics

The proposed methodology involves several crucial steps to analyze sentiment and connotation in Wikipedia biographies over different time periods. Firstly, a curated collection of biographies is meticulously selected to ensure diversity in eras, backgrounds, and significance of individuals. Relevant textual excerpts, including introductions and summaries, are extracted to encapsulate individuals' life stories. The biographical narratives are then segmented into distinct time periods, often guided by significant historical events or contextual shifts. This structured approach allowed us to comprehensively consider how sentiments and connotations evolve, offering insights into public perceptions and biases within biographical information.

Exploring Nuances: Case Studies of Evolving Portrayals

Two case studies exemplify the potency of this methodology. William Eric Aalto's Wikipedia biography passages from 2007 and 2013 demonstrate the impact of linguistic alterations on connotation. The 2007 passage implies a negative association between Aalto's homosexuality and his release from the Office of Strategic Services. In contrast, the 2013 passage adopts a more neutral, procedural tone, signifying changing societal attitudes towards LGBTQ+ rights. This linguistic transformation reflects broader historical shifts in LGBTQ+ acceptance and awareness. Henry D. Abelove's evolving biography showcases shifting perceptions of LGBTQ+ studies. The 2018 passage describes him as an "academic and literary scholar," while the 2023 passage emphasizes his contributions to LGBTQ+ studies and queer theory. This evolution reflects society's increasing recognition of marginalized narratives and acceptance of LGBTQ+ studies as legitimate academic fields.

Implications and Future Directions

The shifts identified in sentiment changes within Wikipedia biographies are closely related to historical events, societal transitions, and media coverage. These nuanced shifts often align with pivotal moments that have shaped public opinions, reflecting broader societal attitudes. Exploring biases and reasons behind connotation frame shifts requires a multifaceted analysis. Historical biases deeply rooted in societal norms can significantly shape language used to describe individuals. The shifts identified in sentiment and connotation frames provide insights into the interchange between language, history, and society in constructing biographical narratives. In a world where digital narratives hold immense sway, scrutinizing sentiment and connotation within evolving Wikipedia biographies is a crucial endeavor. This research report's methodology offers a window into the fluid dynamics of societal perceptions over time. The shifts in language within biographies reflect evolving societal attitudes, encapsulating both individual sentiments and broader cultural shifts. The analysis of William Eric Aalto and Henry D. Abelove's biographies, only small examples, highlights the evolving recognition of LGBTQ+ rights and the power of language to mirror social changes. As digital narratives continue to shape our world, this research becomes an essential tool for exploring the evolution of public perspectives and biases, acting as a bridge between language analysis, societal context, and contemporary communication trends, toward identifying more involved trends in the relationship between language, history, and societal transformation.