Titlebook: Social Informatics; Third International Anwitaman Datta,Stuart Shulman,Ee-Peng Lim Conference proceedings 2011 Springer-Verlag GmbH Berlin

correspondent

飞行员

Digital Media and the Relational Revolution in Social Scienceentury, social scientists have collected stores of data on individual attributes, using surveys and records kept by governments and employers. Individual-level data is also aggregated as population statistics for groups of varying size, from households to nation states, and these data are analyzed u

健壮

Using Web Science to Understand and Enable 21st Century Multidimensional Networksnted exploratorium to model the socio-technical motivations for creating, maintaining, dissolving, and reconstituting multidimensional social networks. Multidimensional networks include multiple types of nodes (people, documents, datasets, tags, etc.) and multiple types of relationships (co-authorsh

音乐会

朦胧

Predicting Market Movements: From Breaking News to Emerging Social Mediasing text mining, breaking news, and social media..In “User-Generated Content on Social Media: Predicting New Product Market Success from Online Word-of-Mouth,” we explore the predictive validity of various text and sentiment measures of online WOM for the market success of new products. The context

反馈

Learning Information Diffusion Models from Observation and Its Application to Behavior Analysisre appropriate to which topic. We use two models, one from push type diffusion (AsIC) and the other from pull type diffusion (AsLT), both of which are extended versions of the well known Independent Cascade (IC) and the Linear Threshold (LT) models that incorporate asynchronous time delay. The model

ROOF

Analysis of Twitter Unfollow: How often Do People Unfollow in Twitter and Why?onship of 1.2 million Korean-speaking users for 51 days and their all tweets. From careful statistical analysis, we confirm that unfollow is prevalent and irrelevant to the volume of interaction. We find that other factors such as link reciprocity, tweet burstiness and informativeness are crucial fo

漂浮

表状态

痛苦一生

Mathematical Continuity in Dynamic Social Networkshe network change is discontinuous it will be so at a single point and the discontinuity will be apparent in that point’s immediate neighborhood. Necessary and sufficient criteria for continuity are provided when the change involves only the addition or deletion of individual nodes or connections (e