Possible Social Media Manipulation Methods

Introduction:

It is becoming more obvious that Social Media and Search Engines on the Internet are resulting in an overall experience that is biased and “washed”.  The observing news outlets aren’t presenting effective arguments that make the public aware, or better, concerned, about the effects of this communication destruction process.  The process of online content manipulation methodologies and potential impacts needs to be explored.  This article presents possible media management methodologies to establish effective means of quashing free speech without anyone being able to prove it, methodologies to change social behaviors and, essentially quash a selected population’s or ideology’s sense of righteousness in their efforts to convey their opinions.

The Highlights:

1.  MUTING METHODS –  Social Media:  There have been words made up for this process, such as “ghost-blocking”, but I like “Muting”.  In essence, the function of Muting a person is a somewhat ingenious process of muting specific individual’s from either being heard, or from hearing from specific respondents. (this word “heard” means “read” in this context”)
2. RATING METHODS- THE PERSON – Social Media: This is becoming commonly known: Rating an individual can go beyond “conservative”, “democrat”, and “independent”.  Individuals can even have ratings as it relates to their relationships with one another.  A person can be “associated” with a person in a way that automated muting would not occur, or would be become a delay, based on a probability that one person would go out of their way to ask the other about how they felt about the communication, via another medium
3. RATING METHODS – THE MESSAGE – Social Media:  It is perceived that this is done now manually, via two controls… Both Hired people that watch content, and volunteer instigated by the “flagging” of a person for “support” regarding another person.  This is an option provided to each user that “opts in”, whether they are the flagged, or the flagger.  Being flagged, whether your message was spot-on and appropriate or not, would instantaneously establish a sub-rating system between one person, and his categorizations, in association to another.  Bringing us to the next item
4. PERSON MONITOR –  Social Media – It is easy for Social Media to justify monitoring of contributor content in order to protect the public from “harmful” messages.  Hell, we asked them to do it.  The problem is that people can report other people, for no reason at all in the apps themselves.  Once this is done, the person reported, for better or worse, now has a shadow (hidden followers – Who is following you?  Can you even see them?), or multiple shadows, all who control rating the person’s messages, blocking, and essentially altering the person’s user experience.
5. HYPERCATEGORIZATION – THE PERSON/MESSAGE:  The number of categories that can be assigned to an individual are numerous and the ability to interlink, or disestablish effective communication for any specific category is staggering.  For instance, any flagged communicators can be blocked from hearing supportive voices as responses to a well thought out message, if their social ideology conflicts with the app provider’s ideology.  The implications of AI that could drive social change around the effective categorization and herding of messages and their users is dangerous.

• SILENCING A VOICE – Search Engines – This one is much easier to do if the Social Media owners are comparing notes with the Search Engine Companies, which they likely are.

1. This one offers a much less glamourous but equally effective method of changing the fabric of free speech.  Search providers can simply make it harder to find one message with a type of category than another.  What else needs to be said?

Case Example of Possible Muting Methods:

The Muting of Free FLOWING Free Speech:  Here are some sample examples of how Muting Techniques could be driven:

1. Flagging a person as someone worthy of “monitoring”
2. Identifying their affiliations in people and their corresponding characteristics
3. Introducing hidden changes to their online experience that may include:
   1. DELAY – Delaying a message from being seen by their intended audience, with no additional controls
   1. BLOCK – Blocking a message from being seen by their intended audience
   1. SUBVERT-MUTE– Display a message only to those who would vehemently argue with their opinion, muting originator’s counter-opinions to the opponents or their supporters
   1. SELECTIVE-EXEMPLIFY – Display their message to all their “rated” supporters (for desired messages), and allow all positively rated respondent’s responses, while denying responses to the contrary
   1. COUNTER-EXEMPLIFY—Display their message to their opponents, only to put the originator into a black hole such as BLOCK, while they still receive the onslaught of disagree-rated respondents, without being able to “fight back”
   1. BLAST-EXEMPLIFY – Display their message for everyone, only to mute the opposition voice.
   1. NOTIFY-NO – This one is where they allow the message to go, but the heavily relied on notification system for that message simply doesn’t fire.  Almost completely invisible from a tracking methodology, and the person’s message is never even seen, while the message “went through just fine”

Conclusion:

While I could cite examples of how such categorization could be hidden from view from authoritative governance, I want to keep this message simple.  People reach out to be heard, and to hear from others.  The sheer ability to make someone perceive nobody liked their message, or nobody decided to respond, or as for Internet, nobody even saw it, is not only a way of Blocking free speech, but making one feel that their speech doesn’t matter.  It goes way beyond a large search provider reminding only Democrats to go vote.  When managed on a microscopic level, (communication by communication), it changes our sense of whether our message is right or wrong, is appreciated or appalled.  I can follow up with the way we can reverse engineer such tracking and blocking systems if you are interested enough to respond.  I do data management for a living, and I’m sure there are checksums that can be quickly established to ensure everybody sees the messages the originator intended them to receive.