Week 13: Future of communications

Algorithms

Filter bubbles

Affordances of digital communication

Affordances: all action possibilities with an object based on users' physical capabilities - the connections of characteristics of the object itself, and how people choose to use it.

What causes media to change?

Changes in the media landscape or ownership structures

Changes in technology: innovation

Changes in norms and values, or composition of society

Technological determinism: the theory that a society's technology determines its cultural values, social structure and history. Aims to provide a causative link between technology and society's nature.

Affordances of digital communication (compared to other forms of communication)

  1. Replicability: we cannot link what we read to its source as easily because of digital communication
  1. Searchability: we can search and find the information we are longing for
  1. Persistence: a step in technology, where it will continue to exist or exist in better terms (e.g. DVD --> Netflix)
  1. Distributability/Scalability: possibility to share information

a situation in which an Internet user encounters only information and opinions that conform to and reinforce their own beliefs, caused by algorithms that personalize an individual's online experience

"it's a bubble of your own unique information, but you can't see what doesn't get into your bubble" (Pariser)

Mathematical method (decision tree), like recipes. Online: Which information (news, advertisement, post evt.) fits best to a specific user

Example: How does Facebook choose what to show in the news feed? What is visible in your feed? Creator (interest of the user in the creator) x Post (this post's performance amongst other users) x Type (type of post - status, photo, link) users prefers) x Recency (how new is the post)

The filter bubble problem

Polarization: a little problem in the EU, but a great problem in the US, where is is a large difference.

Access to digital news: we still get in formation from other sources, like television, in the EU, than social media and algorithms. However, this is different for different age groups, younger generations are more relied on social media as a source for news.

You only see what "people like you" see, and this is accelerated for people with extreme views

Little empirical evidence for filter bubbles in Europe:

... because multi-party systems are less polarized

... because some filters can actually increase diversity

... because most users are still exposed to offline or unfiltered news

... because selecting consonant is as old as the media itself (example is pillarization and selective exposure)

Mis- and disinformation:

Fake news

Definition:

as genre: deliberately created, pseudo-journalistic disinformation

as label: political instrument to delegitimize news media

Misinformation: describes incorrect or misleading in formation that is disseminated unintentionally

Disinformation: incorrect or misleading information that is disseminated deliberately (with intent of misleading by the sender)

Effects of disinformation:

Disinformation is often experienced as credible, especially by older or very young media users

Effects on attitudes and behavior are generally weak: Reasons for this are among other the strong self-selection in the use of disinformation.

If you use media to see news on extreme view or narrow vies, and you keep seeing disinformation, your resilience against this will decrease.

Reasons for quick dissemination (spread) of disinformation on social media

Algorithms prioritize items that recieve many clicks

Content producers earn money per click

Fake news often has a fake high news value (for example surprising, high impact etc.) __> people are more inclined to click on the story

Types of deep fakes:

Face swapping ( identity swapping)

Audio (voice swapping)

Puppetry (mapping a target's face to an actor's for facial re-enhancement)

Lip-synching (synthetic video created to match an audio file and footage of their face)