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Negatives of the environment of the internet

* Rapid attention switching
* Nonlinear information processing
* We pay less attention to information over time
* *Increased* scanning behaviors and selective reading (skimming while reading)
* *Decreased* sustained attention
* Ex. TikToks over a minute are more likely to be skipped
* Alteration (worsening) of deep reading skills

Cognitive offloading

* When people type things into the web (with or without believing it’ll be saved), they are less likely to remember the information; evidence of offloading information onto the computer

Stroop test

* Give a word in a certain color and expect participants to say the color and not the word
* Results were affected whether that word was on their mind or not
* Ex. if it's almost lunch and all the words are foods, people take longer to recall the color
* When the word had to do with a search engine (i.e., “google”), they were also slower because they wish the could google the answer

Conflation of external information and internal knowledge

* People who google things are more likely to think they always knew that information if its “tip-of-the-tongue” info (they feel like they *should* know the answer)

Obscenity

Unprotected speech in any medium

Indecency

Is legal and protected under most circumstances

U.S. v. Thomas: “Amateur Action”

* Husband and wife started a bulletin board system online, including email and downloadable photos, known as “the nastiest place on earth”
* Material was found to be obscene, and they were convicted
* They tried to argue the obscenity law did not apply to intangible materials like electronic files sent over the internet
* Court disagreed, and thus set a precedent that obscenity laws DO apply to the internet and intangible material

CDA (Communications Decency Act)

* Concerned that children could easily be exposed to porn


* “...any communication which is obscene, lewd, lascivious, filthy, or indecent” was deemed illegal

Reno v. ACLU: CDA

* ACLU argued that CDA would limit porn from adults as well (violated their free speech rights), and argued for filtering and blocking tools instead
* Courts agreed and struck down most of the Act, but still claimed obscene material to be illegal
* They decided that the internet differs enough from broadcasting that the same rules shouldn’t apply and it must be protected

COPA (Child Online Protection Act)

* A revamped version of CDA
* Restricted material on the web and on commercial websites as opposed to the web as a whole
* As long as websites asked for credit card information or other screening questions it was okay

Ashcroft v. ACLU: COPA

* ACLU claimed COPA was too vague and that there weren’t enough filtering technologies available to protect minors
* Supreme court deemed that COPA *likely* violates the First Amendment, but did not enforce it

CPPA (Child Pornography Prevention Act)

Expanded the definition of child porn to include youthful looking adults as well as CGI child porn

Ashcroft v. Free Speech Coalition: CPPA

Courts found the new definitional aspects of CPPA to be unconstitutional

CIPA (Children’s Internet Protection Act)

* If schools or libraries wanted to receive federal funding, they needed to block/filter obscene, pornographic, or material deemed harmful to minors
* Applies to visual but not text-based information

U.S. v. American Library Association (ALA): CIPA

* CIPA included public libraries, and because they’d have to block free and public information, ALA took it to court
* Courts upheld CIPA and declared it constitutional

Incitement test

* Looks at certain characteristics of speech to determine whether they should/shouldn’t be banned based on ALL three factors
* Intended to incite violence
* Immediately
* Likely to do so

Planned Parenthood v. American Coalition of Life Activists (2001) “Nuremberg Files”

* Pro-lifers made a website called “Nuremberg Files”
* This website contained addresses, pictures, and other information about clinics and doctors who performed abortions
* These doctors would be assaulted or killed, and the website would be updated to cross out their name or gray it out
* Planned parenthood sued because it was a safety threat
* In 1999, a federal jury sided with Planned Parenthood
* The ACLA appealed it on grounds of First Amendment because the site only *implied* for violence, as opposed to explicitly inciting it
* ACLA was found to be correct unanimously
* In 2002 a circuit court voted six to five to barre the original sites content by arguing they’re advocating violence
* So while advocating for violence is protected, threatening a person is not
* Conclusion is that political hyperbole is protected under the First Amendment, but not true threats
* So ACLA could not do this, and Planned Parenthood won

Section 230 of CDA

* No provider or user of the internet shall be…
* Treated as the publisher or speaker of any information provided by another information content provider
* I.e. COX communication will not be liable for what you say– only you will
* Held liable on account of any action taken to restrict access to material that the provider or user considers to be objectionable
* I.e. FaceBook can block/filter as they see fit

Arguments against Section 230

* Some industries are bound by product safety laws, etc, and the courts have interpreted Section 230 immunity very broadly– which reduces the incentives of online platforms to address illicit activity on their servers
* It leaves them free to moderate lawful content without transparency or accountability
* Courts basically let online platforms do whatever they want, even if it’s not good (making them have no responsibility)
* Everything happening online is speech related (which is legally protected). However, conduct– an activity that can cause harm in the physical world, is both speech and not speech
* Ex. a website that facilitates illegal gun sales would technically be protected under freedom of speech, despite the fact it is an illegal activity/conduct


* Under Section 230 protections, there’s not much accountability for things like products or conducts or business

Gonzales v. Google

* Relatives of victims from an ISIS attack are suing YouTube for helping turn viewers into terrorists because algorithms recommended pro-ISIS content
* Google argued section 230 protects them because they can organize user posts however they want, and that weakening the law would make it harder for them to filter content

SESTA/FOSTA and liability

* They clarify the country’s sex trafficking laws to make it illegal to knowingly assist, facilitate, or support sex trafficking online


* **Exception to the protection of ISP’s and operators**
* So in this case, you ARE responsible and should remove it

Chilling effects

* People don’t exercise free speech because they are afraid of repercussions– often a result of legal rulings like SESTA/FOSTA
* Ex. Craigslist removed a personal section allowing people to seek out other people because they didn’t want to risk them posting something illegal and end up being held liable (instead of filtering, they removed it altogether)

CAN-SPAM (Controlling the Assault of Non-Solicited Pornography and Marketing Act)

* Intention was to limit to amount of spam you get through email
* Certain features of unsolicited commercial email must be present
* It has to be labeled (prohibits false/deceptive headers)
* It has to include a working return email address
* There has to be a valid postal and physical address
* There must be an opt-out option

COPPA (Child Online Privacy Protection Act)

* Response to the fact a lot of websites were aimed towards children and asked for personal information
* COPPA created requirements if sites wanted to target children
* Site operators have to provide notices of what information they are collecting
* They have to obtain parental consent
* Parent’s also now have the option to refuse the collection of information (even retroactively)
* These sites have to protect collected information in secure servers

Intellectual property

* Original works created by individuals or groups
* Intellectual property is protected by copyright law

Copyright origins

U.S. Constitution empowers Congress “to promote the progress of science and useful arts by securing to authors and inventors for limited times exclusive rights to their respective writings and discoveries”

Copyright law: creators

* Exclusive rights
* They can do things with this property that other people cannot

Copyright law: consumers

* Public domain
* Fair use


* First sale

Copyright Act of 1976

* Gave copyright owners the exclusive rights to:
* Reproduce the work
* Prepare derivative works
* Distribute copies of the work to the public
* Perform and display the work publicly
* Perform the work publicly by means of digital audio transmission (added in 1995)

Consumers’ Rights

* **Public domain**: allows for copies to be made by anyone after the copyright term expires
* **First Sale Rule**: allows the owner of a particular copy to sell or otherwise dispose of that copy without the authority of the copyright owner
* Ex. used bookstores
* **Fair Use Doctrine**:
* Allows for some noncommercial copies to be made without the authority of the copyright owner
* Ex. teaching, research, scholarship, etc.

Four Conditions for “Fair Use”

* The purpose and character of the use
* Is it educational? Are you advertising it? Etc.
* The nature of the copyrighted work
* What are you sharing that is copyrighted by others (ex. Is it factual, fictional, easily accessed, out of print? etc.)
* The amount of the work used
* Is it a clip from the movie, or the whole movie? Is it one book chapter? Or the whole book?
* 20% clip of the work is allowed
* The effect of the use on the market value of the work
* Will publishing the work decrease market value? If you post the whole movie, people won’t pay to see the movie

“Betamax” decision (Sony v. Universal City Studios; 1984)

* Sony made a tape recorder that let you make copies to give it to others
* Universal did not like this
* Courts ruled in Sony’s favor, however thinks it has “substantial non-infringing purposes”
* You can use it illegally, but most people aren’t

Napster copyright case (1995)

* Napster allowed users to share MP3 files
* They were sued by studios for copyright infringement
* Napster tried to invoke the Betamax decision, claiming that their technology could be used in plenty of legal ways
* Courts didn’t agree with Napster because most people were using it illegally and they knew it

Copyright enforcement strategies

* They went after individual downloaders of illegal information as opposed to the companies facilitating it (i.e. Napster-like sites)
* This was a PR nightmare for corporations like Sony or Universal who were going after poor people
* Companies switched tactics and started going after ISPs instead because they can see everything you do on the internet

MGM v. Grokster (2001)

* MGM came after Grokster (another Napster-like site), and the courts decided that these companies will be held responsible if they intend on users using it for illegal purposes
* Led to a “chilling effect” where companies shut down even though they weren’t doing illegal stuff because they were afraid a judge wouldn’t see it that way

ISPs and copyright infringement

ISPs are now pursuing a strategy for trying to stop individuals who may be violating copyright law by slowing down their service and sending them a warning and if you continue on after the warning then you get your service cut off completely

Copyright law: licensing

* Shift from ownership to licensing
* This takes away First Sale Rule rights
* Ex. Instead of software companies selling you discs, you now essentially rent them through licensing

Shrinkage of Public Domain

* 1790: you could own something for 28 years before it becomes public domain
* 1909: you could own something for 56 years before it becomes public domain
* 1976: you could own something for your entire life + 50 years for individuals; 75 years for corporations
* 1998: Sonny Bono Copyright Term Extension Act: you could own something for your entire life + 70 yrs for individuals; 95 yrs for corporations
* This was due to lobbying from Disney

Technical Protection Mechanisms

* technology that limits peoples access to copyrighted material
* ex. limited use DVDs
* technologies where you can only play something a certain number of times; technical watermarking
* shift towards protecting creators over consumers

DMCA (Digital Millennium Copyright Act)

* Illegal to circumvent technical protection mechanisms or distribute circumvention tools
* ISPs are *exempt* from liability for copyright infringements by users if they:
* Have no knowledge of violation
* Don’t benefit from it financially
* Act quickly to remove violating material
* Terminate accounts of repeat infringers

Intellectual Property as a Public Good

* The importance of *shared* intellectual property
* Public access to intellectual property is important for the public good; overly aggressive content control threatens both individual freedom and creativity
* Creative commons

Creative commons

You can give permission for certain uses of your copyrighted work without having to get permission every single time

User-generated content

* Online content, provided by and shared among Internet users themselves
* Ex. tiktok, youtube, etc.
* The more people use it, the more everyone benefits from it
* There is more information from more people than ever before


* Participation dynamics
* Few people are sharing information to everyone, even though everyone can
* Ex. wikipedia
* Content self-organization
* No preconception of what things are
* Users can now decide trends, who to cancel, etc.

Current media demographics: Percent online

* Percent online
* 2000-2001, percent increases over time
* Today, 2-3% of adults are not online, majority is

Current media demographics: Education

* Education
* Less education = less use of the internet
* Most likely to use the internet are college graduates

Current media demographics: Income

* Income
* Back then, people who make less money were less likely to use the internet
* Now, there's a huge difference

Current media demographics: Race/ethnicity

* Race/Ethnicity
* Virtually no difference, now lines are crossing

Current media demographics: Age

* Age
* Age difference will matter less in the future because older people will die off

Current media demographics: Sex

* Sex
* Pre-2000, men largely used internet more than women, very little variation in which gender uses more/less internet now
* They do different things online

Current media demographics: Location

* Location
* Rural slightly lags behind, but regardless of where they are, trends are leading upward, the difference is not that big and the gap is closing

Current media demographics: Access

* Access
* Less income = more access to smartphones as opposed to using computers, etc.

Current media demographics: Teenagers

* Teenagers
* Facebook use is trending downward
* Youtube is most popular

Current media demographics: Global

* Global
* 53.4% of people online are in Asia

Instrumental motives (for social media sharing)

* Social motives; norm oriented, expected of people
* Increases over time

Non-instrumental motives (for social media sharing)

* For pleasure or fun
* Decreases over time

Stages of motivation: Social media

* **Initial**
* People motivated and trying it for the first time
* **Sustained**
* People continue to contribute information over time
* **Meta**
* You’ve taken on a leadership role to coordinate other people's efforts; belief in what you’re doing
* Ex. moderator in a chatroom, editor on wikipedia

Contribution feedback & sex differences: **Competitive frame**

* Compare your feedback to others
* Men are more motivated by this type of framing
* Ex. this many people did better than you

Contribution feedback & sex differences: **Cooperative frame**

* How people benefit from your contribution
* Women are more motivated by this type of framing

Contribution feedback & sex differences: Percent/individualistic frame

* Gives you a score on your contribution
* Ex. you did average, above average, or below average

Contribution feedback & sex differences: **Reward mechanisms**

* Badges, money, status, etc. for contributing
* Small monetary rewards actually get people NOT to post as much
* Status works when you’re close to upgrading to the next level, but once you get over the hump, you flatline even if there’s another level
* Peer rewards get people to contribute more, but the quality is not as good anymore

Paralinguistic digital affordances

* Beyond language: votes, thumbs ups, etc
* When people don’t get the reaction they’re hoping for, they rationalize it
* Ex. if your instagram post doesn’t get a lot of likes, you think it’s because you posted at the wrong time or used the wrong filter

Objective social influences in social media

Ex. A doctor’s education, years of practice, certifications, etc.

Subjective social influences in social media

* Ex. A doctors google stars/ratings
* Is found to be more important than objective factors

“Seeding” effects of initial opinions on social media

* If the first rating you see is negative AND inaccurate, you’ll correct/overcome it
* Negative ratings that aren’t controversial are more influential on buyers
* If a positive rating comes first, more positive ratings tend to come after

Emotional influence in social media

* Those who saw more negative words were more likely to post more negative things
* Those who saw more positive words were more likely to post more positive things

Behavioral effects in social media

Ex. People who saw their friends voting on FaceBook would be more likely to go out and vote

The influence of influencers

* The marketing works
* Depends on relatability factors, accessibility, trustworthiness, attractiveness, etc.

Conditions for social influence: warranting theory & warranting value

* Third party endorsement of someone not close to you, the product, business, etc.
* Ex. If I say you should date me because I’m fantastic, it doesn’t mean as much than if someone not close to me said that I’m fantastic and that you should date me

Negative v. positive messages on social media

Negative messages spread faster, but positive messages reach more people

Ideologically diverse information on social media

* Conservatives saw more liberal information on FaceBook than liberals saw conservative information
* Cross-cutting information

**Active vs. Passive use:** Social network use and subjective well-being

* Active: look, and contribute
* Passive: look but don’t contribute
* **Active use is better than passive use**

**Loneliness and causality:** Social network use and subjective well-being

Loneliness makes you use FaceBook

**Mood and affective forecasting errors:** Social network use and subjective well-being

FaceBook use leads to a deterioration of mood over time (feel like you haven't done anything meaningful)

**Account deactivation:** Social network use and subjective well-being

* People paid to deactivate their account found that they did other things like socializing more
* Once they reactivated they didn’t care for it as much
* Their information knowledge decreased
* Higher self esteem
* Reduced political polarization

Data

Collections of individual facts for reference or analysis that represent conditions, ideas, or objects

* Ex. the U.S census, baseball statistics, etc.

History of Data and the web

* There is more stuff available
* Ex. the content of books, blogs, news, etc.
* We have access to old stuff (archives), and new stuff (targeted advertisements, immediate results of sports, etc.)

How much data?

* 20 million hours of YouTube videos per month
* 800 million tweets per day
* 6 billion google searches per day
* “Digital universe” (all data ever captured or created) = \~40 zettabytes

Big Data

* High volume, high velocity, and/or high variety information datasets
* You generate data even if you aren’t trying to
* Simply going on your phone creates data


* Volume, velocity, and variety work together at the same time
* Big Data is interesting because it demonstrates the adaptability from one format to another

Volume

How much stuff is out there

Velocity

* The speed of which things are updated (immediate)
* Ex. trending news is what people are looking at in that moment

Variety

* The type of data that exists varies
* Ex. reactions to movies on twitter vs. cooking blogs

Google flu trends

* Example of big data
* Google relied on people's searches to predict flu outbreaks in the U.S


* They predicted as accurately as the CDC

Where’s George?

* Example of big data


* By entering the serial number on a dollar bill, this website can track where that money has been (ex. Moved from Atlanta, to LA, to Washington, etc.)
* UCSB researchers adapted this website and modeled a new one to track the spread of disease
* It was very accurate

* Social media visualization tools

Foursquare has people check in the locations they’re at, and it tracks people's movements and can makes maps showing what people are doing and when visually as a collective

Wearable devices

Fitbit tracks everything about you

* Where you are, how well you slept, your heart rate, the type of activity you do, etc.

Predictive Analytics

* Examples: 
* Target and pregnant women
* Target noticed women would buy certain things at certain stages of pregnancy and used this data to market to them
* Diapers and beer
* When people bought diapers at night, they would buy beer too, so stores knowing this data would move diapers next to the beer at night


* Orbitz and Macs
* Orbitz would charge more for tickets to people using Macbooks because they probably have more money
* Shopping habits and debtor reliability
* If you bought felt circles for your chair legs and tables, you’re a low credit risk (shows you are responsible)

Social media data and prediction

Using social media, the data can predict your personality, music preferences, political party, etc.

Metadata

* Data about, or beyond, data
* Ex. the data about the aperture speed or time of a photo, as opposed to looking at the actual photo itself


* Draws attention to secondary relationships
* \`Ex. based on the number of pages in the books of a library, they can figure out who the library is catered for (ex. Children, geophysicists, etc.)
* Not looking at the actual content of the book

Critiques of big data

* Non-obvious influences on big data
* Google flu trends got less accurate over time because the search engine started changing (ex. Autofill assuming what you’ll search might not be exactly what you wanted to know)
* Correlation does not equal causation
* Big data can find a lot of correlation, but not causation
* Ex. murder rates and stock prices of internet explorer were very similar in 2008, that doesn’t mean the stock prices were causing murder or vice versa
* Data manipulation
* Ex. google bombing
* By getting a bunch of people to search for certain things, it will increase its ranking
* Ex. getting “miserable failure” as a result when you search up George W. Bush
* Echo-chamber effects
* The same incorrect information is getting perpetuated
* Ex. a wikipedia article that is wrong and hasn’t been corrected yet gets copy and pasted to a reddit thread and now it looks like two separate sources
* Privacy concerns

Credibility

The “believability” of a source, composed of trustworthiness and expertise; subjective not objective

Credibility and the Evolving Media Landscape

* Information abundance
* Nature and number of gatekeepers
* There is no one source that we can trust anymore
* Co-existence of expert information sources and those with “experiential” credibility
* Ex. Both doctors and people who have experienced the illness can be sources of information
* Problematic information validation
* Even if you try to validate information, you can fail and search results may not come up accurately

Medium credibility

* The internet rated second to newspapers in terms of credibility
* The internet was seen as more reliable than tv, radio, etc.

Credibility and Site design/recognition

* Name recognition matters more than site design in terms of sponsor credibility
* However if a site is designed well (mirroring a well known site, such as CNN), study participants found site credibility and message credibility to be fairly similar to an actual source (ex. CNN)
* I.e., If I put crappy information on a good looking website, people will likely believe it

Credibility and Sex differences

* When men and women both evaluated if a man journalist (Jeff) is credible, results did not vary much
* When men and women both evaluated if a woman journalist (Julie) is credible, men found her more credible than Jeff, while women found her less credible than Jeff

Credibility and Information verification

* People don’t verify information often
* When they do, they do the lowest effort, least accurate version of verification

Credibility and Attitudes vs. behaviors

* Those who know they should verify information tend to do it less than everyone else
* College students tend to be better than adult populations at trying to verify the information they see

Credibility and Misinformation

Children were less likely to believe hoax websites

Credibility and Optimistic bias

* You believe you’re more likely to do better than others
* Most people have an optimistic bias (they think they’re better than typical users at identifying credible information, even kids as young as 11)
* Kids never believed they were better than their parents though

Credibility and User-generated content online

* As long as there was a high number of experts or users like you, the information was found to be the same amount of credible
* When there was a low number of experts or users like you, the information was found to be more credible when it came from experts
* When there is a high number of contributions (such as ratings for a movie), you are more likely to believe users like you than experts and rate accordingly to match

Wikipedia information quality

Overall is pretty good