General Purpose Textual Sentiment Analysis and Emotion Detection Tools

Textual sentiment analysis and emotion detection consists in retrieving the sentiment or emotion carried by a text or document. This task can be useful in many domains: opinion mining, prediction, feedbacks, etc. However, building a general purpose tool for doing sentiment analysis and emotion detection raises a number of issues, theoretical issues like the dependence to the domain or to the language but also pratical issues like the emotion representation for interoperability. In this paper we present our sentiment/emotion analysis tools, the way we propose to circumvent the di culties and the applications they are used for.Comment: Workshop on Emotion and Computing (2013

Computational Sociolinguistics: A Survey

Language is a social phenomenon and variation is inherent to its social nature. Recently, there has been a surge of interest within the computational linguistics (CL) community in the social dimension of language. In this article we present a survey of the emerging field of "Computational Sociolinguistics" that reflects this increased interest. We aim to provide a comprehensive overview of CL research on sociolinguistic themes, featuring topics such as the relation between language and social identity, language use in social interaction and multilingual communication. Moreover, we demonstrate the potential for synergy between the research communities involved, by showing how the large-scale data-driven methods that are widely used in CL can complement existing sociolinguistic studies, and how sociolinguistics can inform and challenge the methods and assumptions employed in CL studies. We hope to convey the possible benefits of a closer collaboration between the two communities and conclude with a discussion of open challenges.Comment: To appear in Computational Linguistics. Accepted for publication: 18th February, 201

Sentimental Analysis and Its Applications - A Review

Sentimental Analysis over the years has received a lot of recognition as it has shown a tremendous growth. Nowadays Sentimental analysis can be applied to any field as to bring out the emotions attached to it and also we can be able to know what the other person wants to convey. In our work we will be applying the sentimental analysis on the dataset of 15 hotels from the city and apply the new technique of Statistical Analysis. The Statistical Analysis Technique has taken the attributes like Food Quality, Ambience, area of Location etc into the account for calculating Document Index. The Reviews are taken from a trusted website. It is observed that people before making any decision do visit the reviews before making out the further decisions so e-WOM is the most effective to way to convey the views .Nowadays people rely a lot on electronic form of reviews because it is considered as the most trusted way that people can convey the views

On the Processing and Analysis of Microtexts: From Normalization to Semantics

Trátase dun resumo estendido da ponencia[Abstract] User-generated content published on microblogging social platforms constitutes an invaluable source of information for diverse purposes: health surveillance, business intelligence, political analysis, etc. We present an overview of our work on the field of microtext processing covering the entire pipeline: from input preprocessing to high-level text mining applications.Ministerio de Economía Industria y Competitividad; FFI2014-51978-C2-2-RMinisterio de Economía Industria y Competitividad; TIN2017–85160–C2–1-RMinisterio de Economía Industria y Competitividad; TIN2017–85160–C2–2-RMinisterio de Economía Industria y Competitividad; BES-2015-073768Ministerio de Economía Industria y Competitividad; FFI2014-51978-C2-1-RXunta de Galicia; ED431D 2017/1

Multilingual sentiment analysis in social media.

252 p.This thesis addresses the task of analysing sentiment in messages coming from social media. The ultimate goal was to develop a Sentiment Analysis system for Basque. However, because of the socio-linguistic reality of the Basque language a tool providing only analysis for Basque would not be enough for a real world application. Thus, we set out to develop a multilingual system, including Basque, English, French and Spanish.The thesis addresses the following challenges to build such a system:- Analysing methods for creating Sentiment lexicons, suitable for less resourced languages.- Analysis of social media (specifically Twitter): Tweets pose several challenges in order to understand and extract opinions from such messages. Language identification and microtext normalization are addressed.- Research the state of the art in polarity classification, and develop a supervised classifier that is tested against well known social media benchmarks.- Develop a social media monitor capable of analysing sentiment with respect to specific events, products or organizations

Multilingual sentiment analysis in social media.

252 p.This thesis addresses the task of analysing sentiment in messages coming from social media. The ultimate goal was to develop a Sentiment Analysis system for Basque. However, because of the socio-linguistic reality of the Basque language a tool providing only analysis for Basque would not be enough for a real world application. Thus, we set out to develop a multilingual system, including Basque, English, French and Spanish.The thesis addresses the following challenges to build such a system:- Analysing methods for creating Sentiment lexicons, suitable for less resourced languages.- Analysis of social media (specifically Twitter): Tweets pose several challenges in order to understand and extract opinions from such messages. Language identification and microtext normalization are addressed.- Research the state of the art in polarity classification, and develop a supervised classifier that is tested against well known social media benchmarks.- Develop a social media monitor capable of analysing sentiment with respect to specific events, products or organizations