Paper Info
Title
Adaptive Distribution of Vocabulary Frequencies: A Novel Estimation Suitable for Social Media Corpus
Abstract
This paper aims to propose a mathematical model that evaluates the distribution of the vocabulary frequency terms in proportion to a probabilistic ideal. Once we are able to evaluate it, the main objective of this work is to use it in order to examine text demising. We propose this new metric based on the classic Zipf's law statistic method. The experimental set to test the classic Zipf's law and our developed model is based on some books of the classic literature and some tweets sets of Twitter. Thus, our main result is that the model proposed in this work is more sensitive to the presence of text noises than Zipf's law and is asymptotically quicker, suitable to corpus of social media networks.
Year
DOI
Venue
2014
10.1109/BRACIS.2014.58
Intelligent Systems
Keywords
DocType
Citations 
mathematical analysis,social networking (online),text analysis,Twitter,Zipf law statistic method,adaptive distribution,mathematical model,social media corpus,social media networks,text demising,text noises,tweets sets,vocabulary frequency terms,Information Retrieval,Social Media Networks,Text preprocessing,Zipfs Law
Conference
0
PageRank 
References 
Authors
0.34
11
4
Name
Order
Citations
PageRank
Rodrigo Augusto Igawa1112.58
Guilherme Sakaji Kido200.34
Jose Luis Seixas300.34
Sylvio Barbon44610.97