The role of emotional variables in the classification and prediction of collective social dynamics

We demonstrate the power of data mining techniques for the analysis of collective social dynamics within British Tweets during the Olympic Games 2012. The classification accuracy of online activities related to the successes of British athletes significantly improved when emotional components of tweets were taken into account, but employing emotional variables for activity prediction decreased the classifiers' quality. The approach could be easily adopted for any prediction or classification study with a set of problem-specific variables.

[1]  John J. Grefenstette,et al.  Optimization of Control Parameters for Genetic Algorithms , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  Marija Mitrovic,et al.  Statistical analysis of emotions and opinions at Digg website , 2012, ArXiv.

[3]  Mu-Chen Chen,et al.  Credit scoring with a data mining approach based on support vector machines , 2007, Expert Syst. Appl..

[4]  Zbigniew R. Struzik,et al.  Dynamic structural and topological phase transitions on the Warsaw Stock Exchange: A phenomenological approach , 2013 .

[5]  Assaf Gottlieb,et al.  Algorithm for data clustering in pattern recognition problems based on quantum mechanics. , 2001, Physical review letters.

[6]  Vittorio Loreto,et al.  Collective dynamics of social annotation , 2009, Proceedings of the National Academy of Sciences.

[7]  R Urbanczik,et al.  Universal learning curves of support vector machines. , 2001, Physical review letters.

[8]  Ngoc Thanh Nguyen,et al.  Computational Collective Intelligence. Technologies and Applications , 2014, Lecture Notes in Computer Science.

[9]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[10]  Guillaume Bouchard,et al.  Opinion mining in social media: Modeling, simulating, and forecasting political opinions in the web , 2012, Gov. Inf. Q..

[11]  Johan Bollen,et al.  Twitter mood predicts the stock market , 2010, J. Comput. Sci..

[12]  Zbigniew R. Struzik,et al.  Structural and topological phase transitions on the German Stock Exchange , 2013, 1301.2530.

[13]  David L. Verbyla,et al.  Classification trees: a new discrimination tool , 1987 .

[14]  Jaroslaw Was,et al.  Strategies in crowd and crowd structure , 2012, ArXiv.

[15]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[16]  François Buton,et al.  Directeur de thèse , 2018 .

[17]  N. Lavrac,et al.  Intelligent Data Analysis in Medicine and Pharmacology , 1997 .

[18]  Janusz A. Holyst,et al.  Investment strategy due to the minimization of portfolio noise level by observations of coarse-grained entropy , 2004 .

[19]  Fionn Murtagh,et al.  A History of Cluster Analysis Using the Classification Society's Bibliography Over Four Decades , 2012, ArXiv.

[20]  Mike Thelwall,et al.  Negative emotions boost user activity at BBC forum , 2010, 1011.5459.

[21]  Gerbrand Ceder,et al.  Predicting crystal structure by merging data mining with quantum mechanics , 2006, Nature materials.

[22]  Yen-Liang Chen,et al.  Market basket analysis in a multiple store environment , 2005, Decis. Support Syst..

[23]  Ngoc Thanh Nguyen,et al.  Computational Collective Intelligence. Technologies and Applications , 2012, Lecture Notes in Computer Science.

[24]  P. O'swikecimka,et al.  Effect of detrending on multifractal characteristics , 2012 .

[25]  Mike Thelwall,et al.  Sentiment strength detection for the social web , 2012, J. Assoc. Inf. Sci. Technol..

[26]  J. Kwapień,et al.  Physical approach to complex systems , 2012 .

[27]  Olle Eriksson,et al.  Two-Dimensional Materials from Data Filtering and Ab Initio Calculations , 2013 .

[28]  P. Sobkowicz,et al.  Two-Year Study of Emotion and Communication Patterns in a Highly Polarized Political Discussion Forum , 2012 .

[29]  N. Lavrac,et al.  Intelligent Data Analysis In Medicine And Pharmacology: An Overview , 1997 .

[30]  Shintaro Okazaki,et al.  Extracting Collective Trends from Twitter Using Social-Based Data Mining , 2013, ICCCI.

[31]  Arvid Kappas,et al.  Collective Emotions Online and Their Influence on Community Life , 2011, PloS one.

[32]  Krzysztof Kulakowski,et al.  Indifferents as an interface between Contra and Pro , 2009, 0908.3387.

[33]  Yelena Yesha,et al.  Proceedings of the second international conference on Information and knowledge management , 1993, CIKM 1993.

[34]  Eduardo G. Altmann,et al.  Predictability of Extreme Events in Social Media , 2014, PloS one.

[35]  David Rousseau.  The Software behind the Higgs Boson Discovery , 2012, IEEE Software.

[36]  Li Xiu,et al.  Application of data mining techniques in customer relationship management: A literature review and classification , 2009, Expert Syst. Appl..