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Human Behavior Analysis using Data Science is a natural progression of my background in Computer Science and theme of the projects that I have been involved in as a PhD Student in the Information School during the last 2 years. Reading list for my general exam will consist of research material involving major techniques in data science and the application of the these techniques on the problems related to Social Science.   \\ \section{Methods (Data Science (Machine Learning) Literature)} \begin{enumerate} \begin{itemize} \itemTomaso \item Tomaso  Poggio and Steve Smale (2003). The Mathematics of Learning: Dealing with Data\cite{Poggio_2005} \itemZ \item Z.  Ghahramani (2004). Unsupervised Learning \cite{Ghahramani_2004}\item \cite{Ghahramani_2004}  \item  X. Wu et al. (2008). Top 10 algorithms in data mining \cite{2009} \item Hastie et al. (2009). Elements of Statistical Learning \cite{StatisticalLearning_2009} \item Esther Duflo et al. (2006). Using Randomization in Development Economics Research: A Toolkit \cite{Duflo} \item Rajaraman et al. (2009). Mining of Massive Datasets. \cite{Rajaraman_2009} \item Yaser S. AbuMostafa et al. (2012). Learning from Data \cite{Abu-Mostafa:2012:LD:2207825} \end{enumerate}\item Top 10 algorithms in data mining \cite{2009} \\ \\ \section{Application \item Elements of Statistical Learning \cite{StatisticalLearning_2009} \item Using Randomization in Development Economics Research: A Toolkit \cite{Duflo} \item Rajaraman et al. Mining of Massive Datasets. \cite{Rajaraman_2009} \item Yaser S. AbuMostafa et al. Learning from Data Science to Social Problems} \\ \cite{Abu-Mostafa:2012:LD:2207825} \end{itemize} \section{Application of Data Science to Social Problems}  \subsection{Data Science and Development Economics} \\ \begin{enumerate} \itemEsther Duflo (2000). Schooling and Labor Market Consequences of School Construction in Indonesia: Evidence from an Unusual Policy Experiment \cite{Duflo_2000} \itemDaniel Bjorkegren (2015). The Adoption of Network Goods \cite{Bjorkegren} \end{enumerate} \\ \subsection{Data Science and Measurements} \begin{enumerate} \itemP Deville et al. (2014). Dynamic Population Mapping using Mobile Phone Data\cite{Deville_2014} \itemJoshua Blumenstock et al. (2010). A Method for Estimating the Relationship Between Phone Use and Wealth\cite{blumenstock2010method} \itemV. Frias-Martinez, Jesus Virseda (2012). On the relationship between socio-economic factors and cell phone usage \cite{Frias_Martinez_2012} \itemA. Llorente et al. (2014). Social Media Fingerprints of Unemployment\cite{Llorente_2015} \itemT. Gutierrez et al. (2013). Evaluating socio-economic state of a country analyzing airtime credit and mobile phone datasets\cite{gutierrez2013evaluating} \itemN. Eagle et al. (2010). Network Diversity and Economic Development\cite{eagle2010network} Development \itemDong et al. (2014). Inferring User Demographics and Social Strategies in Mobile Social Networks \cite{Dong:2014:IUD:2623330.2623703} \itemWang et al. (2015). Forecasting Elections with Non-Representative Polls\cite{Wang2015980} \itemC. Smith-Clarke et al. (2014). Poverty on the Cheap: Estimating Poverty Maps Using Aggregated Mobile Communication Networks\cite{Smith-Clarke:2014:PCE:2556288.2557358} \end{enumerate} \\ \subsection{Migration, Mobility and Epidemiology using Big Data} \begin{enumerate} \itemGonzales et al. (2008) Understanding individual human mobility patterns\cite{Gonz_lez_2008} \itemWesolowski et al. (2013). The impact of biases in mobile phone ownership on estimates of human mobility\cite{Wesolowski_2013} mobility \item Blumenstock, JE.(2012). Inferring Patterns of Internal Migration from Mobile Phone Call Records: Evidence from Rwanda\cite{Blumenstock_2012}. Rwanda. \item State, B. et al.(2014). Migration of Professionals to the U.S.: Evidence from LinkedIn Data10.1007/978-3-319-13734-6_37\cite{State_2014} \item Zagheni et al.(2014). Inferring International and Internal Migration Patterns from Twitter Data\cite{Zagheni:2014:III:2567948.2576930} \item Wesolowski, et al.(2012). Quantifying the Impact of Human Mobility on Malaria \cite{Wesolowski_2012} \itemBalcan et al. (2009). Multiscale mobility networks and the spatial spreading of infectious diseases\cite{Balcan_2009} diseases \itemGinsberg et al. (2008). Detecting Influenza Epidemics using Search Engine Query Data\cite{Ginsberg_2008} Data \itemPervaiz et al. (2012). FluBreaks: Early Epidemic Detection from Google Flu Trends\cite{Pervaiz_2012} Trends \itemEagle, Pentland (2005). Reality mining: sensing complex social systems\cite{Eagle_2005} systems \itemOnnela et al. (2007). Structure and tie strengths in mobile communication networks\cite{Onnela_2007} networks \itemOnnela et al. (2014). Using sociometers to quantify social interaction patterns\cite{Onnela_2014} patterns \itemRatti et al. (2010). Redrawing the map of Great Britain from a network of human interactions\cite{Ratti_2010} interactions \itemAmini et al. (2014). The Impact of Social Segregation on Human Mobility in Developing and Urbanized Regions\cite{Amini_2014} Regions \itemOnnela et al. (2011). Geographic constraints on social network groups\cite{Onnela_2011} groups \itemCattuto et al. (2010). Dynamics of person-to-person interactions from distributed RFID sensor networks\cite{Cattuto_2010} networks \itemMuchnik et al. (2013). Social Influence Bias: A Randomized Experiment\cite{Muchnik_2013} \itemAral et al. (2009). Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks\cite{Aral_2009} networks \itemM. Gomez-Rodriguez et al. (2012). Inferring Networks of Diffusion and Influence\cite{Gomez_Rodriguez_2012} Influence \item M. Gomez-Rodriguez et al. (2013). Modeling “Modeling Information Propagation with Survival Theory\cite{rodriguez2013modeling} Theory \itemJ.E. Blumenstock , N. Eagle (2011). Divided We Call: Disparities in Access and Use of Mobile Phones in Rwanda\cite{blumenstock2012divided} Rwanda \item X. Lu et al. (2012). Predictability “Predictability of Population Displacement after the 2010 Haiti Earthquake\cite{Lu_2012} Earthquake \item Bengtsson et al. (2011) Improved "Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti\cite{Bengtsson_2011} \item Gao et al. (2014). Quantifying “Quantifying Information Flow during Emergencies\cite{Gao_2014} Emergencies \item Bagrow et al. 2011). Collective “Collective Response of Human Populations to Large-Scale Emergencies\cite{Bagrow_2011} \item Wang et al. (2014). . Learning to Detect Patterns of Crime\cite{Wang_2013} Crime \item “Precinct or Prejudice? Understanding Racial Disparities in New York City’s Stop-and-Frisk Policy \end{enumerate} \\ \subsection{Data Science, Human Behavior and Networks} \begin{enumerate} \item Quang Duong Jessica Su et al. (2013) . The Effect of Recommendations on Network Structure \item Quang Duong. Sharding Social Networks\cite{Duong_2013} Networks \item Goel, Daniel Goldstein.(2014) Predicting Individual Behavior with Social Networks \cite{Goel_2014} \item Daniel Reeves. Predicting without Markets \end{enumerate} \\ \subsection{Information Flow and Consumption} \begin{enumerate} \item Goel et Seth Flaxman. Filter Bubbles, Chambers and News Conumptions \item Ashton Anderson et. al.(2015). The Structual Virality of Online DiffusionThe Structual Virality of Online Diffusion\cite{Goel_2015} \item Dafna Shahaf, Carlos Guestrin (2012). Connecting the Dots between news articles Shahaf . \cite{Shahaf:2012:CTD:2086737.2086744} \end{enumerate} \\ \subsection{Advertisements and Recommendations} \begin{enumerate} \itemHill et al. (2006). Network-Based Marketing: Identifying Likely Adopters via Consumer Networks\cite{Hill_2006} \item Bhagat et al. (2012). Network-Based Marketing: Identifying Likely Adopters via Consumer Networks \item Maximizing Product Adoption in Social Networks\cite{Bhagat:2012:MPA:2124295.2124368} \end{enumerate}