Research application of the spam filtering and spammer detection algorithms on social media
Вантажиться...
Дата
2022
Автори
Назва журналу
Номер ISSN
Назва тому
Видавець
Анотація
There are a bunch of different social networks and messengers today,
which in times of pandemic corona-virus have take a really big part of our entire live,
especially in our work activities. Besides that, the problem with the spam and
spammers is the most relevant than ever, the count of spam in the work text stream is
continuously increased.
Under spam we understand the text content that is not necessary in the particular
text stream, in case of spammer it is meant the person that is sending the spam
messages in his or her own purposes.
The project was design to solve the scientific and applied problem of detecting
spammers and identifying spam messages in the text context of any social network or
messenger using various spam detection algorithms and spammer detection
approaches. We have implemented 4 algorithms: an algorithm using naive Bayesian
classifier, Support-vector machine, multilayer perceptron neural network and
convolution neural network.
The project was developed in purpose of implementing a spam detection
algorithm that is easy to integrate in a messenger (in our case we used Telegram as an
example). Design algorithm recognizes spam based on the context of a particular text
stream, deletes the spam message and blocks the spammer until one of the application
managers unblock the spammer-user. Since the spam detection task is essentially the
task of sorting messages into two classes, the usage of the design application is not
limited to dealing with spam.
Опис
Oliinyk V. Research application of the spam filtering and spammer detection algorithms on social media / V. Oliinyk ; advisors A. Podorozhniak, N. Liubchenko // Black Sea Science 2022 : proc. of the Intern. Competition of Student Scientific Works / Odesa National University of Technology ; eds. B. Yegorov, M. Mardar [et al.]. – Odessa : ONUT, 2022. – P. 480–494 : tabl., fig. – Ref.: 22 tit.
Ключові слова
spam, social network, naive Bayesian classifier, Support-vector machine, multilayer perceptron neural network, convolution neural network, spammers detection