Choosing the Best Spam Blocker App

The most popular one topping the list is spam. Good thing the spam blocker app is leveling up. When you’re testing apps, you have to be aware that some are more trustworthy than others, so it’s a good idea to be mindful of spammy software developers before you begin, but you can also protect yourself after the event with the right software.

A good spam blocker app nowadays can block up to ninety eight percent of junk email. It also keeps a low rate of false positives, which is highly important so you will not lose official messages. Just remember, though, that it still needs some training so it will know the types of emails it must not filter out.

What To Look For In A Spam Blocker

A good filter marks particular messages if determined spam, then it reports such details back to the network. After which the company does system modification into software updates, thereby improving the accuracy of the filter. Some filters however have difficulties when it comes to mass mailings since they usually have elements that are also found in spam messages.

Understanding How It Really Works

When a spam blocker is well configured, you can depend on it to keep the spam out of your inbox. Even if your filter is working the best possible way it can, there can still be some spam left which you love to see disappear.

On Statistical Filtering

The nature of spam is constantly evolving, so that even the latest spam blocker app filtering out messages basing on its list of keywords, patterns or rules soon become ineffective. Statistical filters try to solve this issue by making their own set of rules while processing your email.

The Apple Mail uses a similar technique called the Adaptive Latent Semantic Analysis or LSA for short. These two techniques compute the probability of a message being a spam based on the content analysis of the current spam and legitimate messages. As time pass by, the accuracy of these techniques increase while they are continuously exposed to new samples of spam and official messages.

They appear to be very similar, Bayesian and LSA filters have distinct differences.

While Bayesian filters depend on straightforward computations of word frequencies, the LSA filters go the extra mile by determining messages, phrases, and words that are spammy in nature basing on the text you yourself identified as junk. LSA filters don’t assign simple weights to words individually; rather, they take it in with regards to the overall context of the word in a given phrase.

The Bottom Line

Some people just give up and choose to live with spam, while others jump from one spam blocker app to another. Others still bother to delve deeper into the problem and actually try to find concrete answers to these problems. Who you want to be among these three is entirely up to you.