Paper Info
Title
Automatically Identifying Changes in the Semantic Orientation of Words
Abstract
The meanings of words are not fixed but in fact undergo change, with new word senses arising and established senses taking on new aspects of meaning or falling out of usage. Two types of semantic change are amelioration and pejoration; in these processes a word sense changes to become more positive or negative, respectively. In this first computational study of amelioration and p ejoration we adapt a web-based method for determining semantic orientation to the task of identifying ameliorations and pejoration s in corpora from differing time periods. We evaluate our proposed method on a small dataset of known historical ameliorations and pejorations, and find it to perform better than a random baseline. Since this te st dataset is small, we conduct a further evaluation on artifi cial examples of amelioration and pejoration, and again find evidence that our proposed method is able to identify changes in semantic orientation. Finally, we conduct a preliminary evaluation in which we apply our methods to the task of finding words which have recently undergone amelioration or pejoration. 1. Detecting changes in semantic orientation Word senses are continually evolving, with both new words and new senses of words arising almost daily. Systems for natural language processing tasks, such as question answer- ing and automatic machine translation, often depend on lex- icons for a variety of information, such as a word's parts- of-speech or meaning representation. When a sense of a word that is not recorded in a system's lexicon is encoun- tered in a text being processed, the system will typically fail to recognize the novel word sense as such, and then incorrectly draw on information from the lexical entry cor- responding to some other sense of that word. The perfor- mance of the entire system will then likely suffer due to this incorrect lexical information. Ideally, a system could aut o- matically identify novel word senses, and subsequently in- fer the necessary lexical information for the computational
Year
Venue
Keywords
2010
LREC 2010 - SEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
machine translation,natural language processing,part of speech
Field
DocType
Citations 
Rule-based machine translation,Computer science,Machine translation,Natural language processing,Artificial intelligence,Word lists by frequency,Sentiment analysis,Lexical item,Speech recognition,Lexicon,Linguistics,Semantics,Semantic change
Conference
15
PageRank 
References 
Authors
1.38
9
2
Name
Order
Citations
PageRank
Paul Cook1755.64
Suzanne Stevenson256664.31