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Artificial intelligence / Sentiment analysis / Computational linguistics / Data analysis / Knowledge / CyberEmotions / Affective computing / Unsupervised learning / General Sentiment / Inc. / Natural language processing / Science / Machine learning


Sentiment Strength Detection for the Social Web This is a preprint of an article published in the Journal of the American Society for Information Science and Technology © copyright 2011 John Wiley & Sons, Inc. Thelwall
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Document Date: 2011-12-15 09:10:42

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File Size: 3,74 MB

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City

Madrid / San Francisco / Genre / Wolverhampton / Lexicon / Philadelphia / Columbus / Barcelona / New York / Washington / DC / Cambridge / Lisbon / London / /

Company

MIT Press / Twitter / Wilson / BBC / Diakopoulos N. A. / MySpace / Last.FM / ACM Press / YouTube / AAAI Press / John Wiley & Sons Inc. / Pearson / B. R. & Smith N. A. / International Language Resources / /

Country

United Kingdom / Israel / Iraq / Palestinian Territories / Iran / Spain / /

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Event

M&A / /

Facility

Stanford University / University of Florida / University of Wolverhampton / University of Sussex / /

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IndustryTerm

opinion mining / Sentiment strength algorithms / sentiment strength detection algorithm / lower accuracy algorithms / short informal social web text / social web data / social web texts / machine learning tools / social web data sets / social web sentiment strength detection / web-derived polarity lexicons / online groups / social web contexts / social web environment / social media / similar algorithms / longer online discussions / machine learning algorithm / web search engines / social Web / important site / social networks / Web This / machine learning algorithms / Data mining emotion / lexical algorithm / sociable and expressive online communication / knowledge management / Data mining / online forums / sentiment analysis algorithms / news discussion site / news identification site / lexical algorithms / social web domains / public social web environment / consumer products / social web context / Bad news travel / online contexts / learning sentiment analysis algorithms / correction algorithm / /

Organization

University of Sussex / hamas / European Union / American Society for Information Science and Technology / Center for Research / MIT / Computational Intelligence / University of Wolverhampton / School of Technology / Stanford University / University of Florida / IEEE Computer Society / Association for Computational Linguistics / /

Person

Barack Obama / Kevan Buckley / George Galloway / Pepe / Mike Thelwall / Morgan Kaufmann / /

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Position

General / author / arbitrator / admiral / /

Product

SentiStrength / /

ProgrammingLanguage

Java / ADA / /

ProvinceOrState

Ohio / Sussex / Pennsylvania / Florida / /

PublishedMedium

the Digg news / Computational Linguistics / the BBC Forum news / Physica A / Lecture Notes in Computer Science / /

Region

Middle East / /

SportsEvent

the 2010 Winter Olympics / /

SportsLeague

Stanford University / /

Technology

RAM / 8 algorithms / 1 algorithm / Sentiment strength algorithms / mobile phones / lexical algorithms / previously selected Multilayer Perceptron algorithm / Java / sentiment strength detection algorithm / training algorithm / 3G / alpha / virtual machine / machine learning algorithms / machine learning algorithm / machine learning / learning sentiment analysis algorithms / two-stage algorithm / cellular telephone / lexical algorithm / Natural Language Processing / knowledge management / sentiment analysis algorithms / spelling correction algorithm / http / Data mining / lower accuracy algorithms / /

URL

http /

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