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Jordan Carpenter

dblp:184/3738 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0001-6918-6286ORCID · corroborated

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

Artificial intelligence and machine learning · 3Databases, data management, data science and information retrieval · 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.

Artificial intelligence
1 paper
Information extraction and text analysis · 77% Trustworthy machine learning · 23%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis › text mining › authorship analysis
author profiling
0.212016
Analyzing Biases in Human Perception of User Age and Gender from Text · ACL (1) 2016
Machine learning › Trustworthy machine learning
fairness
0.112016
Analyzing Biases in Human Perception of User Age and Gender from Text · ACL (1) 2016

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

bias analysis · 0.2
YearPublicationVenuePosition
2016 Analyzing Biases in Human Perception of User Age and Gender from Text
abstract
Lucie Flekova, Jordan Carpenter, Salvatore Giorgi, Lyle Ungar, Daniel Preoţiuc-Pietro. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2016.
Lucie Flek, Jordan Carpenter, Salvatore Giorgi, Lyle H. Ungar, Daniel Preotiuc-Pietro
ACL (1)2
2016 Studying the Dark Triad of Personality through Twitter Behavior
abstract
Research into the darker traits of human nature is growing in interest especially in the context of increased social media usage. This allows users to express themselves to a wider online audience. We study the extent to which the standard model of dark personality -- the dark triad -- consisting of narcissism, psychopathy and Machiavellianism, is related to observable Twitter behavior such as platform usage, posted text and profile image choice. Our results show that we can map various behaviors to psychological theory and study new aspects related to social media usage. Finally, we build a machine learning algorithm that predicts the dark triad of personality in out-of-sample users with reliable accuracy.
Daniel Preotiuc-Pietro, Jordan Carpenter, Salvatore Giorgi, Lyle H. Ungar
CIKM2
2016 An Empirical Exploration of Moral Foundations Theory in Partisan News Sources
Dean Fulgoni, Jordan Carpenter, Lyle H. Ungar, Daniel Preotiuc-Pietro
LREC2