Word and Sentence Level Emotion Analyzation in Telugu Blog and News

Sadanandam, M.

doi:10.5121/ijcsea.2012.2317

Cited by 2 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other papers classify texts according to emotions (Manchala, 2012; Bellegarda, 2013; Staiano and Guerini, 2014). Some of them create their own emotion classifications or use basic classifications already existing in psychology (Scherer and Ekman, 2014; Ekman, 1992; Parrott, 2001).…”

Section: Sentiment Analysis Taxonomymentioning

confidence: 99%

“…The focus of SA research is also diverse. For example, some works classify the texts in sentiments (Jagtap and Pawar, 2013; Yu et al , 2013; Cho et al , 2014), while others (Manchala, 2012; Ruz et al , 2013; Tang et al , 2014) classify in emotions. The emotions are defined as pre-conscious expressions of sentiments, and they are influenced by culture (Bergman, 1998).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A taxonomy for sentiment analysis field

Rodrigues

Camilo-Junior

Rosa

2018

IJWIS

View full text Add to dashboard Cite

Purpose Due to the large and fast growing sentiment analysis (SA) area recently, many new concepts and different nomenclatures have emerged without the desired organization. This confusion in the research field makes the understandability of the concepts hard and also hampers the comparison of different approaches. Thus, this paper aims to propose a hierarchical taxonomy to help the consolidation of SA area. The taxonomy aims at covering the addressed problems and methods in the SA field. Design/methodology/approach This taxonomy is a filtered union of various classifications found in the literature with a proposal of nomenclatures standardization. As instance, a case study is presented with 20 SA-related articles classified according to the proposed taxonomy. Findings This taxonomy is very expressive because it covers many concepts and is also effective once it allows the distinction and categorization of the previous SA works. Originality/value To the best of the authors’ knowledge, the literature does not present such an expressive and effective classification as proposed in this paper. This new taxonomy allows for the navigation between the existing concepts in the SA field as well as, facilitates the search, comparison and indexing of papers already published.

show abstract

Section: Sentiment Analysis Taxonomymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A taxonomy for sentiment analysis field

Rodrigues

Camilo-Junior

Rosa

2018

IJWIS

View full text Add to dashboard Cite

show abstract

Feature based Text Classification using Application Term Set

Nirmala¹,

Pushpa²

2012

IJCA

View full text Add to dashboard Cite

In the present world of information, text classification is a more challenging process due to the larger number of training cases and feature set present in text data. One of the most difficult tasks in the text classification problem is high dimensionality of the feature space. As many real world text classifications are not modeled or too difficult to model, this paper aims at the real world text classification approach or model based on one of the properties of David Merrill's First principles of Instruction (FPI). The Objective is to introduce a method to improve text classifications effectiveness, efficiency and accuracy. In this methodology we categorizes the text using a predefined category group by providing them with the proper training set based on the feature of Application phase in FPI. The algorithm involves the Parsing, text categorization and text analysis. General TermsPattern Recognition, Text Mining, et. al.

show abstract

Word and Sentence Level Emotion Analyzation in Telugu Blog and News

Abstract: Abstract:Emotion analysis, a recent sub discipline at the crossroads of information retrieval

Cited by 2 publications

References 14 publications

A taxonomy for sentiment analysis field

A taxonomy for sentiment analysis field

Feature based Text Classification using Application Term Set

Contact Info

Product

Resources

About