Survival ensembles improve churn prediction in mobile social games.
problem Predicting user churn in mobile social games to retain players.
method Survival analysis and ensemble learning techniques.
result Survival ensembles provide more accurate and robust churn predictions.
Mobile big data contains vast statistical features in various dimensions, including spatial, temporal, and the underlying social domain. Understanding and exploiting the features of mobile data from a social network perspective will be extremely beneficial to wireless networks, from planning, operation, and maintenance…
Mobile sensing is an emerging technology that utilizes agent-participatory data for decision making or state estimation, including multimedia applications. This article investigates the structure of mobile sensing schemes and introduces crowdsourcing methods for mobile sensing. Inspired by social network, one can estab…
Paper presents a churn prediction model for mobile games.
problem Churn prediction for mobile games.
method Semi-supervised and inductive embedding model using deep neural networks.
result Model outperforms existing methods in churn prediction.
Mobile game developers use a scalable churn prediction model to predict player abandonment.
problem Predicting player abandonment in mobile games.
method Survival ensembles approach for accurate churn prediction.
result Accurate predictions on player abandonment and playtime.
Paper analyzes churn behavior in mobile games at micro and macro levels.
problem Understanding churn behavior in mobile games, especially at micro and macro levels.
method Developed a semi-supervised and inductive embedding model for micro-level churn prediction and constructed a relationship graph for macro-level churn ranking.
result Accurate micro-level churn prediction and macro-level churn ranking were achieved using novel techniques.
Social media enhances or diminishes scientific status, depending on usage.
problem Impact of social media on scientific stratification and mobility.
method Logistic Attribution Analysis combining statistical and machine learning methods.
result Social media promotes stratification and mobility, but beyond a threshold, it negatively impacts status.
DASC combines social media and car sensors to improve disaster response.
problem Inconsistent reliability and inconsistent availability of human sensors.
method Hybrid social-car sensing system using game theory, feedback control, and MDP.
result DASC improves detection accuracy and efficiency in disaster response.
Study shows social influence significantly impacts mobile app adoption in African app stores.
problem Understanding social influence on mobile app choices in app stores.
method Developed a structural model combining diffusion and choice models, used Bayesian estimation.
result Customer choices explained better by offline social influence than online density.
AppStreamer reduces mobile game storage by predicting needed files.
problem Expanding storage needs of mobile games and apps.
method Predictive streaming of app files from cloud or edge servers.
result Reduces storage by 87% for Dead Effect 2 and 86% for Fire Emblem Heroes.
System detects social interactions in crowds using mobile phone sensors.
problem Detecting social interactions in crowded settings.
method Multi-modal mobile sensing (BLE, accelerometer, gyroscope) and machine learning.
result 77.8% precision and 86.5% recall for predicting social interactions.
This study evaluates methods for clustering mobile game player behavior data.
problem Clustering time series data of player behavior in free-to-play games.
method Evaluation of various similarity measures and dimensionality reduction techniques.
result Identification and validation of temporal patterns of player behavior.
Mobile phone data predicts users' income levels.
problem Predicting users' income levels from mobile phone data.
method Comparison of feature extraction methods and machine learning techniques.
result Bayesian method based on the communication graph outperforms other methods.
Game aims to improve social interactions for teenagers with ASD.
problem Improving social interactions for teenagers with ASD.
method Presentation of game structure, skeleton detection, and imitation learning methods.
result Game structure and support tools for skeleton detection and imitation learning presented.
Study shows mobile money adoption varies by social groups in Pakistan.
problem Mobile money adoption patterns in Pakistan.
method Analysis of call detail records from a major telecom company.
result User mobility features are crucial for mobile money adoption.
Proposes D2D-LSTM for predicting mobile social network content diffusion paths.
problem Lack of accurate content popularity prediction considering time and location in mobile social networks.
method D2D-LSTM, a deep neural network combining user social features and files features.
result Significantly improved prediction accuracy (up to 85.858%) and faster convergence (less than 100 steps).
Social learning can make financial markets inefficient, but individual learning can fix this.
problem Inefficiencies in financial markets due to social learning.
method Study of the Minority Game model with social and individual learning mechanisms.
result Individual learning can rescue a population from the inefficiencies caused by social learning.
The study proposes that people prioritize status maximization over simple profit maximization in social interactions.
problem The gap between competitive and altruistic human tendencies in social interactions.
method Agent-based model of repeated dictator games in a social network, considering living costs and infractions.
result Individual strategies in the game vary from selfish to selfless, influenced by model parameters.
The study analyzes games and social hierarchies, incorporating luck and depth of competition.
problem Analyzing patterns of wins and losses in games and social hierarchies.
method Generalized probabilistic models incorporating luck and depth of competition.
result Social competition tends to be deeper with many distinct levels, but there is often a chance of upset victories.
Develops a personalized reinforcement learning algorithm for dyadic health interventions.
problem Personalizing health interventions for dyadic relationships in mobile health.
method Dyadic Reinforcement Learning (dyadic RL), a Bayesian and hierarchical online algorithm.
result Established a regret bound and demonstrated empirical performance through simulations and real data.
Predicting and improving player retention is crucial to the success of mobile Free-to-Play games. This paper explores the problem of rapid retention prediction in this context. Heuristic modeling approaches are introduced as a way of building simple rules for predicting short-term retention. Compared to common classifi…
Data on human spatial distribution and movement is essential for understanding and analyzing social systems. However existing sources for this data are lacking in various ways; difficult to access, biased, have poor geographical or temporal resolution, or are significantly delayed. In this paper, we describe how geoloc…
Study predicts traffic congestion based on population mobility data.
problem Predicting traffic congestion in multimodal transport networks.
method Machine learning methods applied to population mobility data.
result Likely prediction of congestion based on population movements.
The paper models crime risk using Foursquare check-ins and mobility data.
problem Understanding and predicting crime risk in urban areas.
method Directed graph of aggregated movement data, region risk factor derivation, DIFFER features.
result Reliable correlations between DIFFER features and crime count observed.
Game teaches ASD teenagers to imitate gestures.
problem Improving social interactions of ASD teenagers.
method Adapted robot-based imitation game with machine learning for pose detection.
result Preliminary results show game can elicit expected responses.
Introduces 'social bow tie' to quantify tie strength in social networks.
problem Understanding tie strength and its influencing factors in social networks.
method Introduced 'social bow tie' framework, defined metrics, used random forests and regression models.
result Bow tie metrics are highly predictive of tie strength, and tie strength is influenced by overlapping and non-overlapping social circles.
This paper studies two important signal processing aspects of equilibrium behavior in non-cooperative games arising in social networks, namely, reinforcement learning and detection of equilibrium play. The first part of the paper presents a reinforcement learning (adaptive filtering) algorithm that facilitates learning…
Study uses mobile phone data to map Chagas disease risk zones.
problem Identifying geographical spread of Chagas disease.
method Analyzing geolocalized call records and public health information.
result Generated risk maps for public health campaigns.
Modeling social conventions from real-time interactions and sensorimotor control.
problem The role of real-time control and learning in social convention formation.
method Control-based Reinforcement Learning (CRL) model grounded in Distributed Adaptive Control (DAC) theory.
result CRL model achieves human-level performance in multi-agent game-theoretic tasks.
Model predicts COVID-19 cases with high accuracy using mobility data.
problem Accurate forecasting of COVID-19 cases for resource management.
method Heterogeneous infection rate model with human mobility, linearization, weighted least squares.
result Extremely accurate predictions of confirmed cases at country and state levels.
Optimistic Hedge achieves optimal regret bounds in two-player zero-sum games.
problem Achieving optimal regret bounds for optimistic Hedge in two-player zero-sum games.
method Refined regret analysis and optimization problem formulation.
result Optimistic Hedge achieves O ( log m log n ) O(\sqrt{\log m \log n}) O ( log m log n ) regret bounds, matching upper and lower bounds. The rise in online social networking has brought about a revolution in social relations. However, its effects on offline interactions and its implications for collective well-being are still not clear and are under-investigated. We study the ecology of online and offline interaction in an evolutionary game framework wh…
Develops a graph-based convolutional network for multi-view networks to improve poverty research.
problem Binary treatment of social network relations in graph learning models.
method Multi-GCN: Graph Convolutional Networks for Multi-View Networks.
result Multi-GCN outperforms state-of-the-art algorithms on poverty prediction tasks and broader multi-view network tasks.
Statistical evaluations of the economic mobility of a society are more difficult than measurements of the income distribution, because they require to follow the evolution of the individuals' income for at least one or two generations. In micro-to-macro theoretical models of economic exchanges based on kinetic equation…
The paper proposes a survival model to optimize mobile notification delivery times.
problem Inappropriate notification timing and interruptions lead to user complaints.
method Developed a state transition framework and a survival model with log-linear and Weibull structures.
result The survival model outperforms logistic regression in prediction accuracy.
DETECT clusters mobility behaviors from trajectories using deep learning.
problem Clustering similar mobility behaviors in large, complex trajectory data.
method DETECT uses deep learning to cluster mobility behaviors from trajectories, transforming and summarizing them to identify similar behaviors.
result DETECT effectively clusters mobility behaviors from real-world datasets.
We study the relationship between social media output and National Football League (NFL) games, using a dataset containing messages from Twitter and NFL game statistics. Specifically, we consider tweets pertaining to specific teams and games in the NFL season and use them alongside statistical game data to build predic…
Unbiased wealth exchanges always lead to inequality.
problem Understanding wealth distribution in unbiased binary exchange systems.
method Analytical demonstration of unbiased binary exchanges leading to perfect inequality.
result Any system driven by unbiased binary exchanges will reach perfect inequality and zero mobility.
Briefly narrates KPR problem and its extensions, useful for resource allocation.
problem Resource allocation problems with many competing agents.
method Theoretical and experimental analysis of KPR problem and its extensions.
result Demonstrates how people analyze and react to complex situations.
We study a networked version of the minority game in which agents can choose to follow the choices made by a neighbouring agent in a social network. We show that for a wide variety of networks a leadership structure always emerges, with most agents following the choice made by a few agents. We find a suitable parameter…
A new method for recommending groups and activities based on geo-social data.
problem Recommendation of groups and activities based on geo-social data with social constraints.
method Proposes an attentive geo-social group recommendation method with an attention mechanism and a spatial query algorithm.
result Significantly outperforms baseline methods in real-world datasets.
Study evaluates how changes in mobility affect COVID-19 case rates.
problem Mixed evidence on mobility-COVID-19 case rate associations.
method Modified treatment policy (MTP) approach with TMLE and Super Learner ensemble.
result Shifts in mobility do not consistently affect subsequent case rates after adjusting for confounders.
Model shows how social norms and individual ethics affect tax evasion.
problem Effects of social norms and individual ethics on tax evasion.
method Agent-based model with simulations of different tax compliance behaviors.
result Threshold levels in society composition explain tax evasion extent.
Study uses Perelman and Ricci flow methods to analyze economic inequality.
problem Impact of socio-economic challenges and technological progress on economic inequality.
method Perelman model and Ricci flow methods.
result Technological innovations and social protection programs reduce inequality.
A new framework for mobile authentication using deep metric learning.
problem Challenges in mobile authentication using behavioral biometrics.
method Deep metric learning, private data protection, flexible training scheduling.
result 95% authentication accuracy on public datasets, robust against attacks.
Survival analysis improves playtime measurement in games.
problem Measuring and improving player retention in games.
method Survival analysis for playtime data without covariates.
result Survival and hazard estimates provide a visual and analytic interpretation of playtime.
Bluetooth data predicts depression severity, showing 18.8% extra variance.
problem Predicting depressive symptom severity using Bluetooth data.
method Extracted 49 Bluetooth features from NBDC data, used linear mixed-effect and hierarchical Bayesian linear regression models.
result Hierarchical Bayesian model achieved best prediction metrics (R2=0.526, RMSE=3.891).
Machine learning detects regime shifts in online game-experiments with high accuracy.
problem Detecting regime shifts in online social systems.
method Gradient-boosted decision trees with memory-retaining features.
result Significantly outperforms standard early warning indicators.