# Structuring the Space of Perspectives

arXiv: https://arxiv.org/abs/2608.12113 · HTML: https://mlsanity.com/paper/2608.12113/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 57 of its 225 references that are in the map.
- First posted on arXiv 12 Aug 2026.

## Builds on (most cited first, 30 of 57)

- [ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks](https://mlsanity.com/paper/2303.15056/) (2023)
- [Parsing Argumentation Structures in Persuasive Essays](https://mlsanity.com/paper/1604.07370/) (2016)
- [We Can Detect Your Bias: Predicting the Political Ideology of News Articles](https://mlsanity.com/paper/2010.05338/) (2020)
- [Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims](https://mlsanity.com/paper/1906.03538/) (2019)
- [In Plain Sight: Media Bias Through the Lens of Factual Reporting](https://mlsanity.com/paper/1909.02670/) (2019)
- [Hierarchical Clustering: Objective Functions and Algorithms](https://mlsanity.com/paper/1704.02147/) (2017)
- [Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception](https://mlsanity.com/paper/2403.14896/) (2024)
- [Beyond prompt brittleness: Evaluating the reliability and consistency of political worldviews in LLMs](https://mlsanity.com/paper/2402.17649/) (2024)
- [Topic Modelling Meets Deep Neural Networks: A Survey](https://mlsanity.com/paper/2103.00498/) (2021)
- [Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies](https://mlsanity.com/paper/1808.09386/) (2018)
- [DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection](https://mlsanity.com/paper/2402.10426/) (2024)
- [Modeling Framing in Immigration Discourse on Social Media](https://mlsanity.com/paper/2104.06443/) (2021)
- [Debate-to-Write: A Persona-Driven Multi-Agent Framework for Diverse Argument Generation](https://mlsanity.com/paper/2406.19643/) (2024)
- [Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions](https://mlsanity.com/paper/2403.01222/) (2024)
- [Identifying Morality Frames in Political Tweets using Relational Learning](https://mlsanity.com/paper/2109.04535/) (2021)
- [A Systematic Media Frame Analysis of 1.5 Million New York Times Articles from 2000 to 2017](https://mlsanity.com/paper/2005.01803/) (2020)
- [Annotator-Centric Active Learning for Subjective NLP Tasks](https://mlsanity.com/paper/2404.15720/) (2024)
- [Scientia Potentia Est -- On the Role of Knowledge in Computational Argumentation](https://mlsanity.com/paper/2107.00281/) (2021)
- [Recommenders with a mission: assessing diversity in newsrecommendations](https://mlsanity.com/paper/2012.10185/) (2020)
- [KGAP: Knowledge Graph Augmented Political Perspective Detection in News Media](https://mlsanity.com/paper/2108.03861/) (2021)
- [Examining Bias in Opinion Summarisation Through the Perspective of Opinion Diversity](https://mlsanity.com/paper/2306.04424/) (2023)
- [Values, Ethics, Morals? On the Use of Moral Concepts in NLP Research](https://mlsanity.com/paper/2310.13915/) (2023)
- [MultiOpEd: A Corpus of Multi-Perspective News Editorials](https://mlsanity.com/paper/2106.02725/) (2021)
- [Assessing Viewpoint Diversity in Search Results Using Ranking Fairness Metrics](https://mlsanity.com/paper/2010.14531/) (2020)
- [Open-World Evaluation for Retrieving Diverse Perspectives](https://mlsanity.com/paper/2409.18110/) (2024)
- [Topic-Specific Sentiment Analysis Can Help Identify Political Ideology](https://mlsanity.com/paper/1810.12897/) (2018)
- [Are "Undocumented Workers" the Same as "Illegal Aliens"? Disentangling Denotation and Connotation in Vector Spaces](https://mlsanity.com/paper/2010.02976/) (2020)
- [An Empirical Analysis of Diversity in Argument Summarization](https://mlsanity.com/paper/2402.01535/) (2024)
- [Voices in a Crowd: Searching for Clusters of Unique Perspectives](https://mlsanity.com/paper/2407.14259/) (2024)
- [GlobeSumm: A Challenging Benchmark Towards Unifying Multi-lingual, Cross-lingual and Multi-document News Summarization](https://mlsanity.com/paper/2410.04087/) (2024)

## Built on by (most cited first, 1 of 1)

- [WildSEEK: Evaluating Language Models for Information-Seeking](https://mlsanity.com/paper/2608.30683/) (2026)

## Abstract (arXiv)

The same event can be reported from different perspectives depending on the experiences, background, and beliefs of the writer or speaker. A variety of NLP areas engage with perspectives, spanning from text analysis to algorithm optimization. A wide range of operative concepts (such as stances, sentiment, frames, and arguments) has been used to capture perspectives in texts, however the precise relationships among those concepts remain unclear. Arguably, a deeper theoretical understanding of these concepts would empower more effective research on perspectives. In this paper, we address this gap by reviewing the space of perspectives in NLP and defining a set of properties that help distinguishing perspective-related concepts. Our analysis leads us to posit a hierarchy which organizes these concepts linearly along a single axis. Finally, we show how this principled conceptual hierarchy can help researchers navigate the field and select operationalizations of perspective that align with their specific research objectives.