ArticlePloS one2021
PyPlutchik: Visualising and comparing emotion-annotated corpora.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Emotional Touchpoints and Emotions of Childbirth: A Systematic Mixed Studies Review and Epistemic Network Analysis.Perspectives on sexual and reproductive health · 2025Pooled it
- Emotion beyond boundaries: How multimodal cues foster cross-cultural affective contagion in immersive livestreaming.PloS one · 2026Article
- A study on the emotional accuracy of generative AI music from the perspective of the "Emotion Wheel" theory.Frontiers in psychology · 2026Article
- Understanding Patient Perceptions of Bacterial Vaginosis Treatments: Mixed Methods Sentiment Analysis Study of Online Drug Review Forums.Online journal of public health informatics · 2025Article
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- EmoAtlas: An emotional network analyzer of texts that merges psychological lexicons, artificial intelligence, and network science.Behavior research methods · 2025Article
- Characterizing the patient experience of physical restraint in psychiatric settings via a linguistic, sentiment, and metaphor analysis.Scientific reports · 2025Article
- Navigating the emotional landscape: exploring caregivers' journey alongside breast cancer survivors with chronic pain.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Article
- Prenatal anxiety recognition model integrating multimodal physiological signal.Scientific reports · 2024Article
- Sentiment Analysis of Patient- and Family-Related Sepsis Events: Exploratory Study.JMIR nursing · 2024Article
- Multimodal driver emotion recognition using motor activity and facial expressions.Frontiers in artificial intelligence · 2024Article
- Visualizing software refactoring using radar charts.Scientific reports · 2023Article
- Patients' Clinical and Psychological Status in Different COVID-19 Waves in Italy: A Quanti-Qualitative Study.Healthcare (Basel, Switzerland) · 2023Article
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- Emotional profiling and cognitive networks unravel how mainstream and alternative press framed AstraZeneca, Pfizer and COVID-19 vaccination campaigns.Scientific reports · 2022Article
- Fat stigma and body objectification: A text analysis approach using social media content.Digital healthArticle
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The increasing availability of textual corpora and data fetched from social networks is fuelling a huge production of works based on the model proposed by psychologist Robert Plutchik, often referred simply as the "Plutchik Wheel". Related researches range from annotation tasks description to emotions detection tools. Visualisation of such emotions is traditionally carried out using the most popular layouts, as bar plots or tables, which are however sub-optimal. The classic representation of the Plutchik's wheel follows the principles of proximity and opposition between pairs of emotions: spatial proximity in this model is also a semantic proximity, as adjacent emotions elicit a complex emotion (a primary dyad) when triggered together; spatial opposition is a semantic opposition as well, as positive emotions are opposite to negative emotions. The most common layouts fail to preserve both features, not to mention the need of visually allowing comparisons between different corpora in a blink of an eye, that is hard with basic design solutions. We introduce PyPlutchik the Pyplutchik package is available as a Github repository (http://github.com/alfonsosemeraro/pyplutchik) or through the installation commands pip or conda. For any enquiry about usage or installation feel free to contact the corresponding author, a Python module specifically designed for the visualisation of Plutchik's emotions in texts or in corpora. PyPlutchik draws the Plutchik's flower with each emotion petal sized after how much that emotion is detected or annotated in the corpus, also representing three degrees of intensity for each of them. Notably, PyPlutchik allows users to display also primary, secondary, tertiary and opposite dyads in a compact, intuitive way. We substantiate our claim that PyPlutchik outperforms other classic visualisations when displaying Plutchik emotions and we showcase a few examples that display our module's most compelling features.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.