ANALYSIS OF REPLIES IN USERS’ SOCIAL MEDIA POSTS.

As parents of an Autist, my spouse and I have received training and learned skills for how to effectively communicate in very literal terms, and to avoid idioms in daily conversations with our brilliant, high-IQ Autist. Learning these skills has also helped us decipher and detect repetition, mimicking, artificial intelligence (AI), bots and cyborgs while using social media.

I’ve been analyzing my state representatives’ social media posts and the replies to them. Some posts are so profoundly false and out of touch with reality they are laughable. Most adults use social media to post their points of view but are forced to do so with brevity due to character limits. It is my opinion limiting characters in posts suppresses the human factor, which might be by design.

Bots are not new to the average IT professional and the average social media user is most-likely ignorant to AI and undoubtedly respond to bots without receiving a comprehensive reply or intellectual debate. I’ve seen some “doozy” replies, which prompted my curiosity and eventual decrease of my replies to social media posts. The differences between an actual human user and a bot have become glaringly evident, especially when posting smack down replies while providing educational facts and links to sources that prove my points of view. Eventually, I grew tired of wasting my time responding to the bots and cyborgs because the rebuttals, agreements, “likes”, “hearts” and debates I was expecting from other user’s just weren’t there. I welcome and prompt a good debate, but not with a bot. Have you ever been labeled as a Russian bot, Putin puppet, bigot, racist, misogynist, white nationalist, etc. on social media?

AI bots, aka “cyborgs” engage in discussions with other users to promote a viewpoint and/or to show support of the original poster/user’s point of view. People are more likely to trust a “blue check mark” account with 1 million Twitter followers than an account with 100.

‘CAREFUL WHO YOU FOLLOW’

Moar:

https://scholar.smu.edu/cgi/viewcontent.cgi?article=1019&context=datasciencereview