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Upendra Kumar

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers
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3

AAAI Conference 2018 Short Paper

Consonant-Vowel Sequences as Subword Units for Code-Mixed Languages

  • Upendra Kumar
  • Vishal Singh
  • Chris Andrew
  • Santhoshini Reddy
  • Amitava Das

In this research work, we develop a state-of-art model for identifying sentiment in Hindi-English code-mixed language. We introduce new phonemic sub-word units for Hindi- English code-mixed text along with a hierarchical deep learning model which uses these sub-word units for predicting sentiment. The results indicate that the model yields a significant increase in accuracy as compared to other models.

IS Journal 2018 Journal Article

Revealing Psycholinguistic Dimensions of Communities in Social Networks

  • Tushar Maheshwari
  • Aishwarya N. Reganti
  • Upendra Kumar
  • Tanmoy Chakraborty
  • Amitava Das

In this paper, the authors seek to answer one fundamental question - what brings people together to form a community? In this article, they explore the personalities (psychological) and values (sociological) of individuals in social network communities in order to understand such natural selection.

AAAI Conference 2017 Short Paper

Semantic Interpretation of Social Network Communities

  • Tushar Maheshwari
  • Aishwarya Reganti
  • Upendra Kumar
  • Tanmoy Chakraborty
  • Amitava Das

A community in a social network is considered to be a group of nodes densely connected internally and sparsely connected externally.Although previous work intensely studied network topology within a community, its semantic interpretation is hardly understood. In this paper, we attempt to understand whether individuals in a community possess similar Personalities, Values and Ethical background. Finally, we show that Personality and Values models could be used as features to discover more accurate community structure compared to the one obtained from only network information.