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Andrés Goméz Emilsson

dblp:151/3270 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational social science and digital humanities › social media analysis
sentiment analysis
0.212014
Sentiment expression conditioned by affective transitions and social forces · KDD 2014

Methods — techniques the papers use, named apart from their topics

statistical modeling · 0.2
YearPublicationVenuePosition
2014 Learning to Reason Pragmatically with Cognitive Limitations
Adam Vogel, Andrés Goméz Emilsson, Michael C. Frank, Daniel Jurafsky, Christopher Potts
CogSci2
2014 Sentiment expression conditioned by affective transitions and social forces
abstract
Human emotional states are not independent but rather proceed along systematic paths governed by both internal, cognitive factors and external, social ones. For example, anxiety often transitions to disappointment, which is likely to sink to depression before rising to happiness and relaxation, and these states are conditioned by the states of others in our communities. Modeling these complex dependencies can yield insights into human emotion and support more powerful sentiment technologies.
Moritz Sudhof, Andrés Goméz Emilsson, Andrew L. Maas, Christopher Potts
KDD2