Abstract:
Since web is expanding day by day and people generally rely on web for
communications, e-mails are the fastest way to send information from one place to another.
Nowadays all the transactions and all the communications whether general or of business
have been taking place through e-mails. E-mail is an effective tool for communication as
it saves a lot of time and cost. But e- mails are also affected by attacks which include Spam
Mails. Spam is the use of electronic messaging systems to send bulk data. Spam is flooding
the Internet with many copies of the same message, in an attempt to force the message on
people who would not otherwise choose to receive it. To avoid this problem mentioned
above, this system is designed to filter the spam message by using sentiment analysis
technique and machine learning approach. The proposed system uses spam words database,
sentiwordnet3.0, and Naïve Bayes classifier is used for training and testing the features and
also evaluating the sentimental polarity. This system is implemented by using Python3.10.
