Aug 23, 2017 · In this paper, we propose an approach to categorize Twitter users into three groups - active, reactive, and inactive targets, based on their ...
In this paper, a new method is proposed for extracting a user's system-wide Sybil-resistant trust value by using the properties embedded in online social ...
ABSTRACT. Online social networks are facing serious threats due to presence of human-behaviour imitating malicious bots (aka socialbots) that.
Apr 9, 2021 · Bibliographic details on Identifying active, reactive, and inactive targets of socialbots in Twitter.
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The proposed approach classifies socialbot targets into three categories viz. active, reactive, and inactive users. We evaluate the proposed approach using ...
Jan 1, 2021 · The proposed approach classifies socialbot targets into three categories viz. active, reactive, and inactive users. We evaluate the proposed ...
Online social networks are facing serious threats due to presence of human-behaviour imitating malicious bots (aka socialbots) that are successful mainly ...
Abulaish, Identifying active, reactive, and inactive targets of socialbots in twitter, in: Proceedings of the 16th Inter- national Conference on Web ...
Identifying active, reactive, and inactive targets of socialbots in twitter ... 2020. A machine learning approach for socialbot targets detection on Twitter.
