Difference between revisions of "Emotion Recognition Algorithms (ERAs)"
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− | Emotion recognition algorithms ( | + | Emotion recognition algorithms (ERAs) are a form of emotion recognition technology and artificial intelligence that recognizes, infers, and harvests "emotions using data sources such as social media behavior, streaming service use, voice, facial expressions, and biometrics..." <ref>Andalibi, Nazanin and Buss, Justin. (2020). ''The Human in Emotion Recognition on Social Media: Attitudes, Outcomes, Risks;'. CHI 2020.</ref>. Emotion recognition algorithms are used in many different contexts including customer service (CITE), employment (CITE), health and wellbeing (CITE), and law enforcement (CITE), and these algorithms can be useful in identifying information pertaining to the context, but they may also be invasive to individuals (CITE). |
== History == | == History == | ||
+ | Emotion recognition roots can be traced back to Paul Ekman<ref>https://en.wikipedia.org/wiki/Paul_Ekman</ref> who, in 1975, identified what he found to be "basic" and "universal" emotions: anger, disgust, fear, joy, sadness, and surprise <ref>Paul Ekman and Wallace V Friesen. 1975. Unmasking the face: A guide to recognizing emotions from facial cues.</ref> | ||
== EAIs on Social Media == | == EAIs on Social Media == | ||
== Benefits and Harms of EAIs == | == Benefits and Harms of EAIs == |
Revision as of 21:21, 25 January 2022
Emotion recognition algorithms (ERAs) are a form of emotion recognition technology and artificial intelligence that recognizes, infers, and harvests "emotions using data sources such as social media behavior, streaming service use, voice, facial expressions, and biometrics..." [1]. Emotion recognition algorithms are used in many different contexts including customer service (CITE), employment (CITE), health and wellbeing (CITE), and law enforcement (CITE), and these algorithms can be useful in identifying information pertaining to the context, but they may also be invasive to individuals (CITE).
History
Emotion recognition roots can be traced back to Paul Ekman[2] who, in 1975, identified what he found to be "basic" and "universal" emotions: anger, disgust, fear, joy, sadness, and surprise [3]
EAIs on Social Media
Benefits and Harms of EAIs
See also
References
- ↑ Andalibi, Nazanin and Buss, Justin. (2020). The Human in Emotion Recognition on Social Media: Attitudes, Outcomes, Risks;'. CHI 2020.
- ↑ https://en.wikipedia.org/wiki/Paul_Ekman
- ↑ Paul Ekman and Wallace V Friesen. 1975. Unmasking the face: A guide to recognizing emotions from facial cues.