Using Instagram Picture Features to Predict Users’ Personality

Ferwerda, Bruce; Schedl, Markus; Tkalčič, Marko

doi:10.1007/978-3-319-27671-7_71

Cited by 55 publications

(81 citation statements)

References 29 publications

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“…Other previous works predicted personality traits from Instagram pictures [14] (with a Root Mean Square Error ranging from 0.66 for Conscientiousness to 0.95 for Neuroticism) and from profile pictures of 100 Facebook users, obtaining an average F1-measure of 67% [5]. An important issue with personality prediction is the relationship between self-assessed and observer-perceived personality types.…”

Section: Related Workmentioning

confidence: 99%

What your Facebook Profile Picture Reveals about your Personality

Segalin

Celli

Polonio

et al. 2017

Proceedings of the 25th ACM International Conference on Multimedia

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People spend considerable effort managing the impressions they give others. Social psychologists have shown that people manage these impressions differently depending upon their personality. Facebook and other social media provide a new forum for this fundamental process; hence, understanding people's behaviour on social media could provide interesting insights on their personality. In this paper we investigate automatic personality recognition from Facebook profile pictures. We analyze the effectiveness of four families of visual features and we discuss some human interpretable patterns that explain the personality traits of the individuals. For example, extroverts and agreeable individuals tend to have warm colored pictures and to exhibit many faces in their portraits, mirroring their inclination to socialize; while neurotic ones have a prevalence of pictures of indoor places. Then, we propose a classification approach to automatically recognize personality traits from these visual features. Finally, we compare the performance of our classification approach to the one obtained by human raters and we show that computer-based classifications are significantly more accurate than averaged human-based classifications for Extraversion and Neuroticism.

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Section: Related Workmentioning

confidence: 99%

What your Facebook Profile Picture Reveals about your Personality

Segalin

Celli

Polonio

et al. 2017

Proceedings of the 25th ACM International Conference on Multimedia

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“…The contributions of this work to personality research comes in two fold: 1) we extend prior research by Ferwerda et al [11,13] by exploring the predictive value of personality in the content features of Instagram pictures, and 2) we explore whether combining visual features with content features improves personality prediction of Instagram users.…”

Section: Introductionmentioning

confidence: 97%

“…1 With the use of picture filters, Instagram allows its users to create and express a distinct personal style by adjusting and manipulating the appearance of the content they want to share. Previous work of Ferwerda et al [11,13] on predicting personality traits from Instagram pictures extracted the visual features of Instagram pictures and showed that these properties consist of personality information of users. A few other work showed that personality can be predicted from pictures.…”

Section: Introductionmentioning

confidence: 99%

Predicting Users' Personality from Instagram Pictures

Ferwerda

Tkalčič

2018

Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization

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Instagram is a popular social networking application that allows users to express themselves through the uploaded content and the different filters they can apply. In this study we look at personality prediction from Instagram picture features. We explore two different features that can be extracted from pictures: 1) visual features (e.g., hue, valence, saturation), and 2) content features (i.e., the content of the pictures). To collect data, we conducted an online survey where we asked participants to fill in a personality questionnaire and grant us access to their Instagram account through the Instagram API. We gathered 54,962 pictures of 193 Instagram users. With our results we show that visual and content features can be used to predict personality from and perform in general equally well. Combining the two however does not result in an increased predictive power. Seemingly, they are not adding more value than they already consist of independently.

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“…Similarly as the case of personality perception, personality recognition have been addressed in the literature using different data modalities, i.e., still images [50], [96], [97], image sequences [98], [99], audiovisual (with [11], [59], [79], [85], [86], [100], [101], [102], [103] or without [88], [104] interactions) and multimodal [105], [106], [107], [108].…”

Section: Automatic Personality Recognitionmentioning

confidence: 99%

“…Taking the popularity of social networks into account, Ferwerda et al [96] proposed to infer real personality from the way users manipulate their pictures on Instagram. However, the work is basically limited to color information analysis.…”

Section: Automatic Personality Recognitionmentioning

confidence: 99%

First Impressions: A Survey on Vision-Based Apparent Personality Trait Analysis

Jacques

Güçlütürk

Pérez

et al. 2022

IEEE Trans. Affective Comput.

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Personality analysis has been widely studied in psychology, neuropsychology, and signal processing fields, among others. From the past few years, it also became an attractive research area in visual computing. From the computational point of view, by far speech and text have been the most considered cues of information for analyzing personality. However, recently there has been an increasing interest from the computer vision community in analyzing personality from visual data. Recent computer vision approaches are able to accurately analyze human faces, body postures and behaviors, and use these information to infer apparent personality traits. Because of the overwhelming research interest in this topic, and of the potential impact that this sort of methods could have in society, we present in this paper an up-to-date review of existing vision-based approaches for apparent personality trait recognition. We describe seminal and cutting edge works on the subject, discussing and comparing their distinctive features and limitations. Future venues of research in the field are identified and discussed. Furthermore, aspects on the subjectivity in data labeling/evaluation, as well as current datasets and challenges organized to push the research on the field are reviewed.

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Using Instagram Picture Features to Predict Users’ Personality

Cited by 55 publications

References 29 publications

What your Facebook Profile Picture Reveals about your Personality

What your Facebook Profile Picture Reveals about your Personality

Predicting Users' Personality from Instagram Pictures

First Impressions: A Survey on Vision-Based Apparent Personality Trait Analysis

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