Contributo in volume, 2012, ENG, 10.1007/978-3-642-34228-8_22
Muntean C. I., Morar G. A., Moldovan D.
CNR-ISTI, Pisa, Italy; Babes-Bolyai University, Cluj-Napoca, Romania; Babes-Bolyai University, Cluj-Napoca, Romania;
Social networks are generators of large amount of data produced by users, who are not limited with respect to the content of the information they exchange. The data generated can be a good indicator of trends and topic preferences among users. In our paper we focus on analyzing and representing hashtags by the corpus in which they appear. We cluster a large set of hashtags using K-means on map reduce in order to process data in a distributed manner. Our intention is to retrieve connections that might exist between different hashtags and their textual representation, and grasp their semantics through the main topics they occur with.
clustering, hashtag, k-means, twitter
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
ID: 215621
Year: 2012
Type: Contributo in volume
Creation: 2013-05-21 14:56:17.000
Last update: 2015-02-23 15:25:21.000
CNR authors
External links
OAI-PMH: Dublin Core
OAI-PMH: Mods
OAI-PMH: RDF
DOI: 10.1007/978-3-642-34228-8_22
URL: http://link.springer.com/chapter/10.1007%2F978-3-642-34228-8_22?LI=true
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:215621
DOI: 10.1007/978-3-642-34228-8_22
Scopus: 2-s2.0-84868383433
ISI Web of Science (WOS): 000345282300022
PUMA: 2012-A1-027