TY - GEN
T1 - Investigating crowdsourcing as a method to collect emotion labels for images
AU - Korovina, Olga
AU - Casati, Fabio
AU - Baez, Marcos
AU - Berestneva, Olga
AU - Nielek, Radoslaw
PY - 2018/4/20
Y1 - 2018/4/20
N2 - Labeling images is essential towards enabling the search and organization of digital media. This is true for both "factual", objective tags such as time, place and people, as well as for subjective, such as the emotion. Indeed, the ability to associate emotions to images is one of the key functionality most image analysis services today strive to provide. In this paper we study how emotion labels for images can be crowdsourced and uncover limitations of the approach commonly used to gather training data today, that of harvesting images and tags from social media.
AB - Labeling images is essential towards enabling the search and organization of digital media. This is true for both "factual", objective tags such as time, place and people, as well as for subjective, such as the emotion. Indeed, the ability to associate emotions to images is one of the key functionality most image analysis services today strive to provide. In this paper we study how emotion labels for images can be crowdsourced and uncover limitations of the approach commonly used to gather training data today, that of harvesting images and tags from social media.
KW - Crowdsourcing
KW - Emotions
KW - Image tagging
KW - Subjective tasks
UR - http://www.scopus.com/inward/record.url?scp=85052019457&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85052019457&partnerID=8YFLogxK
U2 - 10.1145/3170427.3188667
DO - 10.1145/3170427.3188667
M3 - Conference contribution
AN - SCOPUS:85052019457
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2018 CHI Conference on Human Factors in Computing Systems, CHI EA 2018
Y2 - 21 April 2018 through 26 April 2018
ER -