… Narayanan and Shmatikov [22] demonstrated that user identification can be accomplished
by relying on network topology information; however, the user identification performance …

… -detection, trend identification, trust management, user-modeling in online social media. …
companies use twitter for advertisement, these people usually create lots of spam information …

… -one user identification. Furthermore, we show that using the optimal method for identification
indeed gives higher identification … in resisting user identification attacks on these datasets. …

… aimed to identify a set of influential nodes via information entropy. Firstly, the information
entropy of … Then, select the node with the largest information entropy and renovate its l-length …

… identify user groups; Secondly, we propose a noise filter based on information entropy to
reduce … in this paper has a higher performance for user group identification, and provide a good …

… In Section 4.2, we apply the Δ-entropy criterion in system identification with quantized I/O
data. The estimation of distribution algorithm (EDA) is used as the parameter search algorithm, …

… the entropy evaluation and introduce user coherence by taking the relative differences between
ratings into account. We will show that the information entropy … if we identify the potential …

… an entropy-based guideline for open dataset. In the guideline, we introduce a re-identification …
It means that the entropy is how much information we need to identify data. In other words, …

… a user attributes’ susceptibility and entropy based … unique identifications of multiple users
(ie, users’ community) caused by the highly susceptible QIs. We adapt the information entropy …

… The attributes considered for the analytics are Twitter User ID, Time, Time-zone, Tweet,
Geo-location, URL, retweet count, replies, followers. After pre-processing the tweets, word …