Aligning Multidimensional Worldviews and Discovering Ideological Differences (2021)

Abstract: The Internet is home to thousands of communities, each with their own unique worldview and associated ideological differences. With new communities constantly emerging and serving as ideological birthplaces, battlegrounds, and bunkers, it is critical to develop a framework for understanding worldviews and ideological distinction. Most existing work, however, takes a predetermined view based on political polarization: the “right vs. left” dichotomy of U.S. politics. In reality, both political polarization – and worldviews more broadly – transcend one-dimensional difference, and deserve a more complete analysis. Extending the ability of word embedding models to capture the semantic and cultural characteristics of their training corpora, we propose a novel method for discovering the multifaceted ideological and worldview characteristics of communities. Using over 1B comments collected from the largest communities on Reddit.com representing ~40% of Reddit activity, we demonstrate the efficacy of this approach to uncover complex ideological differences across multiple axes of polarization.

## introduction and motivation tractatus @xcite media choice, social networking platforms, and collaborative filtering on the internet have enabled individuals to enter "echo chambers" that reflect shared worldviews @xcite @xcite . the internet also publicly reveals these communities and their communication for analysts of language, culture and interaction at unprecedented scale. despite the abundance of such data, however, analysis of worldviews and ideological difference has been dominated by considerations of "polarization" @xcite ; bail figure 1 : by training the model to align "candidate", "politics", and "corrupt," a hypothesis alignment f ("trump"|c 1 ) ≈ f ("clinton"|c 2 ) emerges. here, we draw inspiration from the approach of interpretive anthropology and the focus of cognitive anthropology to represent, investigate and compare worldviews from community discourse. in the interpretation of cultures, geertz rendered culture as "a system of inherited conceptions expressed in symbolic forms by means of which men communicate, perpetuate, and develop their knowledge about and attitudes toward life" @xcite . combined with cognitive anthropology's concern with how implicit knowledge changes the way people perceive and relate to the world (d' @xcite , this motivates assessment of worldviews through modern pre-trained natural language models that render words @xcite and phrases @xcite in relation to one another as a function of their proximity in discourse. when pre-trained on the discourse of distinctive communities, these models have begun to enable a highly resolved evaluation of expressed worldviews -symbol systems that reveal shared patterns of attention and association @xcite . based in the premise that the language a community uses carries markers of the culture of that community @xcite , recent work has demonstrated the ability of trained embedding models to uncover cultural values @xcite @xcite . however, these models are limited by requiring significant researcher input to query the model for insights. recent work has also demonstrated the potential to embed communities themselves @xcite , but has not extended to the level of a word-level understanding of community worldview. we instead model community language as a specific instance of an ideological dialect (or, an "ideolect") 1 . using a similar approach to @xcite , which identified single-axis polarized political "languages" on youtube, we introduce a new method for unsupervised cultural analysis based on multilingual embedding alignment. our method provides high-accuracy alignment, is the first to analyze multiple facets of ideological polarization, and readily enables analysis in a large multi-community setting -which we demonstrate by identifying multiple axes of ideological differences on reddit. as an additional contribution, we publish a github repository with all the code necessary to replicate this work and apply our methods in new settings. 2 this repository also includes tables of results that were too long to reasonably include in this paper. ## unsupervised cultural analysis in this section, we summarize previous approaches to the analysis of cultural values through word embedding models. ## data reddit serves as the primary source of data for this project. the platform is structured as a collection of peer-driven communities called "subreddits," ostensibly self-regulated by norms decided upon by members of the subreddit and enforced by moderators. all users are anonymous, can be a part of multiple subreddits, and are free to create their own. as such, user comments serve as a rich source of conversation and discourse across varied interests and topics, organized into communities of self-selected individuals. the structure of reddit lends itself to a community-focused analysis of language, with the site's use of self-enforced boundaries allowing us to observe discourse across groups without having to define the notion of a group ourselves. instead, we rely on every user's own choice about where they wish to engage, and where to post their comments. this multi-community setting has been exploited in the past by researchers, with @xcite exploring the contours of multi-community engagement and the widening of interests via a user's exploration of different subreddits over time. @xcite explore the norms of interaction dictated and enforced by multiple "toxic" subreddits, showcasing how self-selection and preentry learning play a key role in sustaining these norms. @xcite explicitly study negative mobilizations between different subreddits as conflict, finding that they tend to occur between communities that are highly similar in content. ## modeling and aligning ideological dialects we conceive of the alignment procedure as a matching of "conceptual anchors," designed to align the worldview of two communities. if two communities, c a and c b , have identical worldviews, we expect that structural relations between words will be preserved across the community boundary. however, if they have different worldviews, we would expect that the words central to that conflict would not align well, even when anchoring words are well-aligned. ## exploring worldview and ideology in this section, we use our method to perform a number of sociolinguistic explorations. ## conclusion in this paper we have demonstrated a novel technique for unsupervised cultural analysis by building upon existing work treating word embeddings as tools to explore worldview, as well as work on multilingual embedding alignment. we have shown that our formulation is flexible, and able to operate effectively in a complex multi-community setting. we have also demonstrated a number of useful applications of the worldview discovery procedure, from the automatic identification of axes of polarization, to the identification of out-of-vocabulary words with similar semantics, to the large-scale analysis of an online social community with multiple dimensions of ideological polarization.