Twitter mood predicts the stock market.
TLDR
This work investigates whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time and indicates that the accuracy of DJIA predictions can be significantly improved by the inclusion of specific public mood dimensions but not others.About:
This article is published in Journal of Computational Science.The article was published on 2011-03-01 and is currently open access. It has received 4453 citations till now. The article focuses on the topics: Mood & Affect (psychology).read more
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Sentiment Analysis and Opinion Mining
TL;DR: Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language as discussed by the authors and is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining.
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Data mining with big data
TL;DR: A HACE theorem is presented that characterizes the features of the Big Data revolution, and a Big Data processing model is proposed, from the data mining perspective, which involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations.
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The Parable of Google Flu: Traps in Big Data Analysis
David Lazer,Ryan Kennedy,Ryan Kennedy,Ryan Kennedy,Gary King,Alessandro Vespignani,Alessandro Vespignani +6 more
TL;DR: Large errors in flu prediction were largely avoidable, which offers lessons for the use of big data.
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Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach
H. Andrew Schwartz,Johannes C. Eichstaedt,Margaret L. Kern,Lukasz Dziurzynski,Stephanie M. Ramones,Megha Agrawal,Achal Shah,Michal Kosinski,David Stillwell,Martin E. P. Seligman,Lyle H. Ungar +10 more
TL;DR: This represents the largest study, by an order of magnitude, of language and personality, and found striking variations in language with personality, gender, and age.
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The rise of social bots
TL;DR: In this article, the authors discuss the threat posed by today's social bots and how their presence can endanger online ecosystems as well as our society, and how to deal with them.
References
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Prospect theory: an analysis of decision under risk
Daniel Kahneman,Amos Tversky +1 more
TL;DR: In this paper, the authors present a critique of expected utility theory as a descriptive model of decision making under risk, and develop an alternative model, called prospect theory, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights.
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Prospect theory: analysis of decision under risk
Daniel Kahneman,Amos Tversky +1 more
Journal ArticleDOI
ANFIS: adaptive-network-based fuzzy inference system
TL;DR: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference System implemented in the framework of adaptive networks.
Book
Descartes' Error: Emotion, Reason, and the Human Brain
TL;DR: The authors argued that rational decisions are not the product of logic alone - they require the support of emotion and feeling, drawing on his experience with neurological patients affected with brain damage, Dr Damasio showed how absence of emotions and feelings can break down rationality.