SentiFul: A lexicon for sentiment analysis

Alena Neviarouskaya*, Helmut Prendinger, Mitsuru Ishizuka

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

144 Citations (Scopus)


In this paper, we describe methods to automatically generate and score a new sentiment lexicon, called SentiFul, and expand it through direct synonymy and antonymy relations, hyponymy relations, derivation, and compounding with known lexical units. We propose to distinguish four types of affixes (used to derive new words) depending on the role they play with regard to sentiment features: propagating, reversing, intensifying, and weakening. Besides derivation, we considered important process of finding new words such as compounding, which is a highly productive process, especially in the case of nouns and adjectives. We elaborated the algorithm for automatic extraction of new sentiment-related compounds from WordNet using words from SentiFul as seeds for sentiment-carrying base components and applying the patterns of compound formations. In the paper, the importance of considering modifiers, contextual valence shifters, and modal operators, which are integral parts of the SentiFul lexicon for robust sentiment analysis, is also discussed.

Original languageEnglish
Article number5708128
Pages (from-to)22-36
Number of pages15
JournalIEEE Transactions on Affective Computing
Issue number1
Publication statusPublished - 2011 Jan
Externally publishedYes


  • Linguistic processing
  • mining methods and algorithms
  • thesauruses

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction


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