Name
Abstract | ||
|---|---|---|
We introduce a crowd-powered approach for the creation of a lexicon for any theme given a set of seed words that cover a variety of concepts within the theme. Terms are initially sorted by automatically clustering their embeddings and subsequently rearranged by crowd workers in order to create a tree structure. This type of organization captures hierarchical relationships between concepts and allows for a tunable level of specificity when using the lexicon to collect measurements from a piece of text. We use a lexicon expansion method to increase the overall coverage of the produced resource. Using our proposed approach, we create a hierarchical lexicon of personal values and evaluate its internal and external consistency. We release this novel resource to the community as a tool for measuring value content within text corpora. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-01129-1_28 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Lexicon induction,Crowd sourcing,Personal values | Data mining,Computer science,Text corpus,Lexicon,Tree structure,Natural language processing,Artificial intelligence,Cluster analysis | Conference |
Volume | ISSN | Citations |
11185 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steven R. Wilson | 1 | 12 | 7.21 |
| Yiting Shen | 2 | 0 | 0.34 |
| Rada Mihalcea | 3 | 6460 | 445.54 |