Reliability of crowdsourcing as a method for collecting emotions labels on pictures

Korovina, Olga; Báez, Marcos; Casati, Fabio

doi:10.1186/s13104-019-4764-4

Cited by 6 publications

(2 citation statements)

References 13 publications

(10 reference statements)

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“…SAM is a non-verbal, pictorial (figure-based) scale, with three items to assess the valence, arousal, and dominance associated with the reaction to an emotional experience. Previous research suggests that participants may experience difficulty understanding how to rate their emotional experience (particularly in the dominance dimension) based on the pictorial response scale (e.g., Korovina et al, 2019). To address this difficulty, we added a label for the lowest and highest point of each dimension.…”

Section: Emotional Experiencementioning

confidence: 99%

As Strong as We Are United: Effects of Intrapersonal and Interpersonal Emotion Regulation on Quality of Life in Women With Breast Cancer

2021

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Women diagnosed with breast cancer often experience unpleasant emotions, resulting in higher levels of emotional burden and decreased levels of wellbeing and quality of life. The present correlational and cross-sectional study aims to compare the implementation of two regulatory levels, intrapersonal and interpersonal (as social sharing of emotions), and two types of strategies, antecedent-focused and response-focused, and explore their impact on breast cancer patients’ perception of quality of life. Sixty-eight women previously diagnosed with the disease participated in this study, with a mean age of 63years old (SD=11.58). Data were collected through a self-report questionnaire to assess emotional experience, intrapersonal regulation, social sharing of emotions, and breast cancer-related wellbeing and quality of life. Data yielded that most of the participants regulated their negative emotions within social interactions and made more use of antecedent-focused strategies to cognitively reformulate the emotional episode. Social and family wellbeing were positively associated with antecedent-focused strategies, as well as intrapersonal and interpersonal regulatory levels. Moreover, the occurrence of sharing episodes and social interactions played an important and beneficial role on patients’ perceived quality of life. These findings reinforce the importance of promoting an adaptive intrapersonal regulation among breast cancer patients. Results also suggest that social sharing of emotions is an efficient process to help them to better cope with the psychological and emotional burden of the disease, thus positively influencing the way they perceive their social and family wellbeing, as well as their quality of life.

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Section: Emotional Experiencementioning

confidence: 99%

As Strong as We Are United: Effects of Intrapersonal and Interpersonal Emotion Regulation on Quality of Life in Women With Breast Cancer

2021

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“…The abundance of contents available online, such as TV-shows and movies, allows researchers to glean rich emotion data representative of various contexts efficiently. Crowdsourcing further supports inexpensive data annotation while serving as another data source 40 , 41 . Datasets of this type have advantages in sample size and the diversity of subjects, but generalizability remains an issue.…”

Section: Background and Summarymentioning

confidence: 99%

K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations

et al. 2020

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Recognizing emotions during social interactions has many potential applications with the popularization of low-cost mobile sensors, but a challenge remains with the lack of naturalistic affective interaction data. Most existing emotion datasets do not support studying idiosyncratic emotions arising in the wild as they were collected in constrained environments. Therefore, studying emotions in the context of social interactions requires a novel dataset, and K-EmoCon is such a multimodal dataset with comprehensive annotations of continuous emotions during naturalistic conversations. The dataset contains multimodal measurements, including audiovisual recordings, EEG, and peripheral physiological signals, acquired with off-the-shelf devices from 16 sessions of approximately 10-minute long paired debates on a social issue. Distinct from previous datasets, it includes emotion annotations from all three available perspectives: self, debate partner, and external observers. Raters annotated emotional displays at intervals of every 5 seconds while viewing the debate footage, in terms of arousal-valence and 18 additional categorical emotions. The resulting K-EmoCon is the first publicly available emotion dataset accommodating the multiperspective assessment of emotions during social interactions.

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Training Affective Computer Vision Models by Crowdsourcing Soft-Target Labels

et al. 2021

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Reliability of crowdsourcing as a method for collecting emotions labels on pictures

Cited by 6 publications

References 13 publications

As Strong as We Are United: Effects of Intrapersonal and Interpersonal Emotion Regulation on Quality of Life in Women With Breast Cancer

As Strong as We Are United: Effects of Intrapersonal and Interpersonal Emotion Regulation on Quality of Life in Women With Breast Cancer

K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations

Training Affective Computer Vision Models by Crowdsourcing Soft-Target Labels

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