… of user generated content; and (iii) embedding based on user name, real name and description.
Using a Twitter and Flickr dataset of users and their posting … of user identification across …

… function to identify the periodicity of the posting time series. Then we study the individual …
Thus we believe the hourly posting pattern can be a good feature for predicting users’ …

… [27] utilized statuses and comments posted by users to implement user identification across
… behavior pattern in order to solve the user identification problem. Li et al. [29] designed a …

… pattern mining-based cross-social network user identification algorithm that analyzes …
User-generated data-based user identification mainly relies on the timing of blog postings, the …

… data at a snapshot and have not gone for analysis of user … time sequenced data of user tweet
communication to identify non-… In order to identify this threshold we use iterative clustering. …

… user posting behavior at an individual (micro) level and apply LDA to cluster user temporal
patterns and … , we study individual user’s posting behaviors and identify their hidden patterns. …

… messages written by an active user in the same period… identify these robot accounts using
a classification approach based on a number of observable features related to activity patterns …

… the differences between posting and click patterns in a … We find that these behavioral signals
– posting versus clicking – … posting behaviors influence clicks, for each URL, we identify …

… , better understanding of user posting behavior has become … at providing a global picture
of user activity patterns on these … To identify emerging news on Twitter, we borrow the idea …

… then use the expectation-maximization (EM) algorithm to identify … uncertainty levels in
online-postings. Our approach reveals the … We use the real-world data from online-postings to …