2016 · 31 citations · 30 references
This paper provides a binary, token-based classification of German particle verbs (PVs) into literal vs. non-literal usage. A random forest improving standard features (e.g., bagof-words; affective ratings) with PV-specific information and abstraction over common nouns significantly outperforms the majority baseline. In addition, PV-specific classification experiments demonstrate the role of shared particle semantics and semantically related base verbs in PV meaning shifts.
30
A comparison of event models for naive bayes text classification
Andrew McCallum, Kamal Nigam · 1998 · 3.2K citations
Measuring praise and criticism
Peter D. Turney, Michael L. Littman · ACM Transactions on Information Systems · 2003 · 1.5K citations