"Twitter Sentiment in Data Streams with Perceptron"
written by Nathan Aston, Jacob Liddle, Wei Hu,
published by Journal of Computer and Communications, Vol.2 No.3, 2014
has been cited by the following article(s):
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[1] 1W A bibliometric analysis on tourist destinations research
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[2] An Intelligent Dashboard for Assisted Tweet Composition in the Cultural Heritage Area (Work-in-progress)
[3] New Approach for Detecting Spammers on Twitter using Machine Learning Framework
[4] تنقیب بیانات وسائل التواصل الإجتماعى واستخداماته فى البحوث الإعلامیة... تحلیل المشاعر نموذجاً‎
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[7] Tweet Sentiment Analysis (TSA) for Cloud Providers Using Classification Algorithms and Latent Semantic Analysis
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[10] Sentimental Analysis of Demonetization Over Twitter Data Using Machine Learning
[11] Evaluating Active Learning Sampling Strategies for Opinion Mining in Brazilian Politics Corpora
[12] Basic Review of Different Strategies for Sentiment Analysis in Online Social Networks
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[13] Opinion Mining and Active Learning: a Comparison of Sampling Strategies
[14] Eating disorders studied over online social networks
[15] Análise de sentimento em tweets
[16] BrainT at IEST 2018: Fine-tuning Multiclass Perceptron For Implicit Emotion Classification
[17] Multilingual Sentiment Analysis for a Swiss Gig
[18] Clinical Communication and Collaboration: Three Essays Examining the Impact of IT Interventions on At-Risk Populations Using Healthcare Analytics
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[19] A Review of Sentiment Semantic Analysis Technology and Progress
[20] The Use of Hashtags in the Promotion of Art Exhibitions
[21] Design of Machine Learning Approach For Spam Tweet Detection
[22] Smart Card Adoption in Healthcare: An Experimental Survey Design using Message Framing
[23] Design and simulation of a novel classification framework for separating sentiment from assorted game related tweets
[24] Like it or not: A survey of twitter sentiment analysis methods
ACM Computing Surveys (CSUR), 2016
[25] Influência dos sentimentos dos turistas nos social media para o desenvolvimento do turismo
[26] A bibliometrics analysis on tourist destinations research
[27] 大数据分析中的计算智能研究现状与展望
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[28] Tourist Clusters, Destinations and Competitiveness
[29] 1 A bibliometric analysis on tourist destinations research
Tourist Clusters, Destinations and Competitiveness: Theoretical Issues and Empirical Evidences, 2015
[30] A trust-based sentiment delivering calculation method in microblog
International Journal of Services Technology and Management, 2015
[31] A bibliometric analysis on tourist destinations research: focus on destination management and tourist cluster
[32] Understanding and monitoring attitudes of product properties over time
Dissertation, 2015
[33] Tourist Clusters, Destinations and Competitiveness: Theoretical Issues and Empirical Evidences
[34] # Worldcup2014 on Twitter
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[35] Talking about Climate Change and Global Warming
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[36] A era de um mercado social
[37] Sentiment Analysis on the Social Networks Using Stream Algorithms
Journal of Data Analysis and Information Processing, 2014
[38] Corpus-Based Information Extraction and Opinion Mining for the Restaurant Recommendation System
Statistical Language and Speech Processing. Springer International Publishing,, 2014
[39] Content-Based Sentiment and Geolocation Tagging of Social Media Messages for Trend Analysis
The Fifth International Workshop on Mining Ubiquitous and Social Environments. 2014., 2014
[40] Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks