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Social Computing, Behavioral-Cultural Modeling and Prediction

Overview of attention for book
Cover of 'Social Computing, Behavioral-Cultural Modeling and Prediction'

Table of Contents

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    Book Overview
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    Chapter 1 The Evolution of Paternal Care
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    Chapter 2 Parent Training Resource Allocation Optimization Using an Agent-Based Model of Child Maltreatment
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    Chapter 3 Influence and Power in Group Interactions
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    Chapter 4 The Marketcast Method for Aggregating Prediction Market Forecasts
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    Chapter 5 Peer Nominations and Its Relation to Interactions in a Computer Game
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    Chapter 6 Predicting Personality Using Novel Mobile Phone-Based Metrics
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    Chapter 7 Social Computing, Behavioral-Cultural Modeling and Prediction
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    Chapter 8 An Agent-Based Model for Simultaneous Phone and SMS Traffic over Time
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    Chapter 9 Reconstructing Online Behaviors by Effort Minimization
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    Chapter 10 “Copping” in Heroin Markets: The Hidden Information Costs of Indirect Sales and Why They Matter
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    Chapter 11 Cultural Polarization and the Role of Extremist Agents: A Simple Simulation Model
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    Chapter 12 Using Imageability and Topic Chaining to Locate Metaphors in Linguistic Corpora
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    Chapter 13 Automated Trading in Prediction Markets
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    Chapter 14 Social Network Analysis of Peer Effects on Binge Drinking among U.S. Adolescents
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    Chapter 15 Feedback Dynamic between Emotional Reinforcement and Healthy Eating: An Application of the Reciprocal Markov Model
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    Chapter 16 Testing the Foundations of Quantal Response Equilibrium
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    Chapter 17 Modeling the Social Response to a Disease Outbreak
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    Chapter 18 Discovering Consumer Health Expressions from Consumer-Contributed Content
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    Chapter 19 Patient-Centered Information Extraction for Effective Search on Healthcare Forum
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    Chapter 20 Controlling for Population Variances in Health and Exposure Risk Using Randomized Matrix Based Mathematical Modeling
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    Chapter 21 How Do E-Patients Connect Online? A Study of Social Support Roles in Health Social Networking
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    Chapter 22 Dynamic stochastic blockmodels: Statistical models for time-evolving networks
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    Chapter 23 LA-LDA: A Limited Attention Topic Model for Social Recommendation
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    Chapter 24 Graph Formation Effects on Social Welfare and Inequality in a Networked Resource Game
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    Chapter 25 Recommendation in Reciprocal and Bipartite Social Networks–A Case Study of Online Dating
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    Chapter 26 In You We Follow: Determining the Group Leader in Dialogue
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    Chapter 27 Pareto Distance for Multi-layer Network Analysis
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    Chapter 28 Formation of Multiple Networks
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    Chapter 29 A Flexible Framework for Probabilistic Models of Social Trust
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    Chapter 30 Social Computing, Behavioral-Cultural Modeling and Prediction
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    Chapter 31 Massive Media Event Data Analysis to Assess World-Wide Political Conflict and Instability
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    Chapter 32 Sparsification and Sampling of Networks for Collective Classification
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    Chapter 33 A Comparative Study of Social Media and Traditional Polling in the Egyptian Uprising of 2011
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    Chapter 34 Hashtag Lifespan and Social Networks during the London Riots
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    Chapter 35 A Text Cube Approach to Human, Social and Cultural Behavior in the Twitter Stream
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    Chapter 36 Mapping Cyber-Collective Action among Female Muslim Bloggers for the Women to Drive Movement
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    Chapter 37 Discovering Patterns in Social Networks with Graph Matching Algorithms
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    Chapter 38 Critiquing Text Analysis in Social Modeling: Best Practices, Limitations, and New Frontiers
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    Chapter 39 Which Targets to Contact First to Maximize Influence over Social Network
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    Chapter 40 Intruder or Welcome Friend: Inferring Group Membership in Online Social Networks
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    Chapter 41 Identifying Influential Twitter Users in the 2011 Egyptian Revolution
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    Chapter 42 Analytical Methods to Investigate the Effects of External Influence on Socio-Cultural Opinion Evolution
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    Chapter 43 Who Shall We Follow in Twitter for Cyber Vulnerability?
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    Chapter 44 Respondent-Driven Sampling in Online Social Networks
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    Chapter 45 Trade-Offs in Social and Behavioral Modeling in Mobile Networks
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    Chapter 46 Privacy Protection in Personalized Web Search: A Peer Group-Based Approach
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    Chapter 47 Detecting Anomalous Behaviors Using Structural Properties of Social Networks
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    Chapter 48 Measuring User Credibility in Social Media
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    Chapter 49 Financial Crisis, Omori’s Law, and Negative Entropy Flow
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    Chapter 50 Trust Metrics and Results for Social Media Analysis
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    Chapter 51 Predicting Mobile Call Behavior via Subspace Methods
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    Chapter 52 Modeling the Interaction between Emergency Communications and Behavior in the Aftermath of a Disaster
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    Chapter 53 Modeling the Dynamics of Dengue Fever
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    Chapter 54 Improving Markov Chain Monte Carlo Estimation with Agent-Based Models
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    Chapter 55 Geographic Profiling of Criminal Groups for Military Cordon and Search
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    Chapter 56 Exploiting User Model Diversity in Forecast Aggregation
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    Chapter 57 Risk-Based Models of Attacker Behavior in Cybersecurity
Attention for Chapter 6: Predicting Personality Using Novel Mobile Phone-Based Metrics
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

3 news outlets
1 blog
1 patent


24 Dimensions

Readers on

282 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Predicting Personality Using Novel Mobile Phone-Based Metrics
Chapter number 6
Book title
Social Computing, Behavioral-Cultural Modeling and Prediction
Published in
Lecture notes in computer science, January 2013
DOI 10.1007/978-3-642-37210-0_6
Book ISBNs
978-3-64-237209-4, 978-3-64-237210-0

Yves-Alexandre de Montjoye, Jordi Quoidbach, Florent Robic, Alex (Sandy) Pentland, de Montjoye, Yves-Alexandre, Quoidbach, Jordi, Robic, Florent, Pentland, Alex (Sandy)


Ariel M. Greenberg, William G. Kennedy, Nathan D. Bos

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 282 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 3%
Spain 4 1%
United Kingdom 2 <1%
Austria 2 <1%
Germany 1 <1%
France 1 <1%
Malaysia 1 <1%
Switzerland 1 <1%
India 1 <1%
Other 3 1%
Unknown 257 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 67 24%
Student > Master 51 18%
Researcher 38 13%
Student > Bachelor 24 9%
Student > Doctoral Student 19 7%
Other 49 17%
Unknown 34 12%
Readers by discipline Count As %
Computer Science 102 36%
Psychology 32 11%
Social Sciences 21 7%
Engineering 21 7%
Economics, Econometrics and Finance 15 5%
Other 45 16%
Unknown 46 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 34. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 January 2023.
All research outputs
of 23,549,388 outputs
Outputs from Lecture notes in computer science
of 8,139 outputs
Outputs of similar age
of 284,861 outputs
Outputs of similar age from Lecture notes in computer science
of 317 outputs
Altmetric has tracked 23,549,388 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,139 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 284,861 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 317 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.