Empirical analysis of collective human behavior for extraordinary events in blogosphere

Abstract

To uncover underlying mechanism of collective human dynamics, we survey more than 1.8 billion blog entries and observe the statistical properties of word appearances. We focus on words that show dynamic growth and decay with a tendency to diverge on a certain day. After careful pretreatment and fitting method, we found power laws generally approximate the functional forms of growth and decay with various exponents values between -0.1 and -2.5. We also observe news words whose frequency increase suddenly and decay following power laws. In order to explain these dynamics, we propose a simple model of posting blogs involving a keyword, and its validity is checked directly from the data. The model suggests that bloggers are not only responding to the latest number of blogs but also suffering deadline pressure from the divergence day. Our empirical results can be used for predicting the number of blogs in advance and for estimating the period to return to the normal fluctuation level.

10 pages, 19 figures

References in corpus (7)

• Power-law distributions in empirical data
• Robust dynamic classes revealed by measuring the response function of a social system
• Social Structure of Facebook Networks
• Dynamics of conflicts in Wikipedia
• Circadian pattern and burstiness in mobile phone communication
• Scaling breakdown in flow fluctuations on complex networks
• Pareto law of the expenditure of a person in convenience stores

Cited by in corpus (13)

• Statistical Laws Governing Fluctuations in Word Use from Word Birth to Word Death
• Computational Socioeconomics
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• Probing the statistical properties of unknown texts: application to the Voynich Manuscript
• A model of spreading of sudden events on social networks
• Measuring and Modeling Behavioral Decision Dynamics in Collective Evacuation
• Empirical observations of ultraslow diffusion driven by the fractional dynamics in languages: Dynamical statistical properties of word counts of already popular words
• Statistical properties of fluctuations of time series representing the appearance of words in nationwide blog data and their applications: An example of observations and the modelling of fluctuation scalings of nonstationary time series
• A power-law decay model with autocorrelation for posting data to social networking services
• A Dynamical Model of Twitter Activity Profiles
• A minor extension of the logistic equation for growth of word counts on online media: Parametric description of diversity of growth phenomena in society
• In Quest of Significance: Identifying Types of Twitter Sentiment Events that Predict Spikes in Sales
• Relations between anomalous diffusion and fluctuation scaling: The case of ultraslow diffusion and time-scale-independent fluctuation scaling in language