Personal Information
Entreprise/Lieu de travail
Dayton, Ohio United States
Profession
Graduate Student/Research Assistant
Secteur d’activité
Technology / Software / Internet
À propos
My name is Lu Chen and I am a PhD student at the Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis Center) at Wright State University. My advisor is Dr. Amit P. Sheth.
I am broadly interested in Text Mining, Natural Language Processing (NLP) and Social Media Analytics, with a particular focus on Sentiment Analysis and Extraction of Subjective Information. My research applies multidisciplinary methods to understand people, e.g., who they are, what they think, how they feel, etc., through analyzing what they say and how they behave in social media space.
Mots-clés
emotion analysis
data cleansing
active learning
sentiment analysis
subjective information extraction
religion
social media
computational social science
twitter
sentiment analysis;subjective information extracti
twitter;election prediction;social meida;public op
Tout plus
Présentations
(5)J’aime
(3)What's up at Kno.e.sis?
Amit Sheth
•
il y a 9 ans
U.S. Religious Landscape on Twitter
Lu Chen
•
il y a 9 ans
Are Twitter Users Equal in Predicting Elections? Insights from Republican Primaries and 2012 General Election
Artificial Intelligence Institute at UofSC
•
il y a 11 ans
Personal Information
Entreprise/Lieu de travail
Dayton, Ohio United States
Profession
Graduate Student/Research Assistant
Secteur d’activité
Technology / Software / Internet
À propos
My name is Lu Chen and I am a PhD student at the Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis Center) at Wright State University. My advisor is Dr. Amit P. Sheth.
I am broadly interested in Text Mining, Natural Language Processing (NLP) and Social Media Analytics, with a particular focus on Sentiment Analysis and Extraction of Subjective Information. My research applies multidisciplinary methods to understand people, e.g., who they are, what they think, how they feel, etc., through analyzing what they say and how they behave in social media space.
Mots-clés
emotion analysis
data cleansing
active learning
sentiment analysis
subjective information extraction
religion
social media
computational social science
twitter
sentiment analysis;subjective information extracti
twitter;election prediction;social meida;public op
Tout plus