The An automatic real – time email spammer detection and fake data identification on social media
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Abstract
Social networking sites have a tremendous influence on the lives of millions of people every
day. A large number of popular social networking sites have been hijacked by spammers,
who are utilising them to transmit a wide range of harmful and meaningless content. allowing
a large number of spam messages to be delivered. Fake Twitter accounts send out spammy
tweets to real people in order to promote products or websites. Users and resources are both
harmed by this practise. An rising number of people are utilising phoney IDs to send out
dangerous drugs, making it easier for them to distribute them. When it comes to online social
networks, Twitter studies are becoming more prominent (OSNs). Twitter spammers are
examined in this study. User attributes (e.g. content characteristics, graph features), structural
aspects (such as the graph's structure), as well as temporal characteristics, may be split down
into four groups (such as how long the tweets are active). This webpage is a helpful resource
for researchers who are looking for the most current information on Twitter spam detection.
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