Refine
Year of publication
- 2017 (2) (remove)
Document Type
- Part of a Book (1)
- Conference Proceeding (1)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Institute
Web archives created by the Internet Archive (IA) (https://archive.org), national libraries and other archiving services contain large amounts of information collected for a time period of over twenty years. These archives constitute a valuable source for research in many disciplines, including the digital humanities and the historical sciences by offering a unique possibility to look into past events and their representation on the Web.
Most Web archive services aim to capture the entire Web (IA) or national top-level domains and are therefore broad in their scope, diverse regarding the topics they contain and the time intervals they cover. Due to the large size and the broad scope it is difficult for interested researchers to locate relevant information in the archives as search facilities are very limited. Many users are more interested in studying smaller and topically coherent event-centric collections of documents contained in a Web archive [1,2]. Such collections can reflect specific events such as elections, or natural disasters, e.g. the Fukushima nuclear disaster (2011) or the German federal elections.
We present a method for detecting word sense changes by utilizing automatically induced word senses. Our method works on the level of individual senses and allows a word to have e.g. one stable sense and then add a novel sense that later experiences change. Senses are grouped based on polysemy to find linguistic concepts and we can find broadening and narrowing as well as novel (polysemous and homonymic) senses. We evaluate on a testset, present recall and estimates of the time between expected and found change.