CMN 172 Final Cumulative Exam - Dr. Brunner, UC Davis
UPDATED ACTUAL Questions and CORRECT Answers
Warranting Principle - pertains to the perceived legitimacy and validity of info seen about another
person online
- in virtual environments, info that is easily manipulated has much less warranting
value
- ex: bio info, altered photos, etc
- higher likelihood that it is false info
- we are more likely to trust info that is harder to falsify
- ex: degrees, links to UC websites
- higher warranting value
- more likely to be true
- Self-Generated content holds less warranting value than Other-Generated
content
- Self-Generated = bio info, posts, status updates
- Other-Generated = comments, other people talking about your traits
Catfishing - scammer gets you to trust them by using a fake account and then asks for $$$
- 25% of women admit to being a catfish
- 38% of men admit to being a catfish
- Men are more likely to catfish
- more than 50% of the US admit to catfishing
- ex: Manti Te'o Catfishing Incident
- affordances of editability (lying) and persistence (catching them in the lie) are
important here
Why Do People Catfish? - Revenge
- Loneliness
- Lower self-esteem
- Attachment style
- anxious = more likely to be victim and the perpetrator of catfishing
- anxious people crave intimacy but fear rejection
- avoidant people are independent and fear intimacy
Deception - deliberately inducing in another person a belief that you know to be false
- requires intent to lie
,4-Factor Model of Deception 1) Attempted Control
- deceivers will try to control their verbal + nonverbal behavior
- if comm looks to perfect/fluent, could be indicative of deception
2) Felt Emotion
- people who lie may experience anxiety and fear of getting caught
- truth-tellers also experience anxiety of not being believed
- ex: Duping Delight
- when the emotions don't fit the circumstances, could be deception
3) Physiological Arousal
- changes in breathing, heartbeat, pupil dilation, skin conductance
- if you have a baseline of their behavior you can catch this easier
4) Cognitive Processing
- leakage may come from inability to remember all the details of a lie
- longer and more detailed lies that are complete fabrication are easy to catch
Duping Delight - feeling happy when you get away with lying
- can result in micro-expressions of happiness while talking about sad shit
Interpersonal Deception Theory (Burgoon, 1996) - deceivers will look for indications that a receiver is suspicious
- receivers will look for indications that others are deceiving them
- detecting suspicions is easier and less socially costly than detecting lies
- calling someone out on their lies is socially costly and possibly inappropriate
- receivers show suspicion and the deceivers then modify their behavior to be less
suspicious
- the deceivers and receivers each modify their behavior based on the other
person's behavior
Data on How Difficult it is to Detect Deception - on average, people are 54% accurate in detecting lies
- most people have a ton of (misplaced) confidence in their lie-detecting abilities
- when CMC + high stakes, we suck at detecting deception cause they will take
more time to craft a believable lie
- on average, over CMCs, people are 8-20% accurate in detecting deception
Why We Suck At Lie-Detection 1) Competent Liars Alter Their Behavior
- they modify their behavior when detecting suspicion to lower that suspicion and
sell the lie
- "Counter-Measures"
2) No Pinocchio Nose
- there is no consistent, reliable behavior that we can look to to know that
someone is lying
3) Truth Bias
- we have an expectation that people close to us will be truthful to us
- that lets them lie easier to us
Counter-Measures - when liars match the posture and behaviors of the people they're lying to
- helps build rapport and sell the lie
, Curvilinear Curve of Detecting Deception - acquaintances are the best at lie detection
- people close to us give in to the truth bias
- people we don't know at all have no baseline for our behavior
- acquaintances are the best cause they have a baseline of our behavior but they
don't have truth bias
Types of Digital Deception 1) Identity-Based Deception
(i) Identity Concealment
- aspects of our identity are omitted or altered
- ex: presenting false age, lie about height and $ status
(ii) Identity Theft
- take someone else's identity and present it as our own
- ex: catfishing
(iii) Identity Forgery
- take lots of info from many sources to craft a brand new identity
- ex: spam, phishing, robocalls
2) Message-Based Deception
- lying about the content of our messages, also they know my real identity
- ex: "I got a flat tire" when I don't
3 Types of False Online Information 1) Fake News
- happens a lot now with AI
2) Rumors
- tabloids, lies in media
3) Fake Reviewers
- fake online reviews
- Astro-Turfing
Astroturfing - when you work for a business and give it a great online review
- pretend to be a customer
2 Types of Luring 1) Spamming
- not really nefarious
- ex: junk emails, spam emails
2) Phishing
- very nefarious/dangerous
- ex: trying to obtain sensitive info
- ex: bank info, passwords, SSI#
UPDATED ACTUAL Questions and CORRECT Answers
Warranting Principle - pertains to the perceived legitimacy and validity of info seen about another
person online
- in virtual environments, info that is easily manipulated has much less warranting
value
- ex: bio info, altered photos, etc
- higher likelihood that it is false info
- we are more likely to trust info that is harder to falsify
- ex: degrees, links to UC websites
- higher warranting value
- more likely to be true
- Self-Generated content holds less warranting value than Other-Generated
content
- Self-Generated = bio info, posts, status updates
- Other-Generated = comments, other people talking about your traits
Catfishing - scammer gets you to trust them by using a fake account and then asks for $$$
- 25% of women admit to being a catfish
- 38% of men admit to being a catfish
- Men are more likely to catfish
- more than 50% of the US admit to catfishing
- ex: Manti Te'o Catfishing Incident
- affordances of editability (lying) and persistence (catching them in the lie) are
important here
Why Do People Catfish? - Revenge
- Loneliness
- Lower self-esteem
- Attachment style
- anxious = more likely to be victim and the perpetrator of catfishing
- anxious people crave intimacy but fear rejection
- avoidant people are independent and fear intimacy
Deception - deliberately inducing in another person a belief that you know to be false
- requires intent to lie
,4-Factor Model of Deception 1) Attempted Control
- deceivers will try to control their verbal + nonverbal behavior
- if comm looks to perfect/fluent, could be indicative of deception
2) Felt Emotion
- people who lie may experience anxiety and fear of getting caught
- truth-tellers also experience anxiety of not being believed
- ex: Duping Delight
- when the emotions don't fit the circumstances, could be deception
3) Physiological Arousal
- changes in breathing, heartbeat, pupil dilation, skin conductance
- if you have a baseline of their behavior you can catch this easier
4) Cognitive Processing
- leakage may come from inability to remember all the details of a lie
- longer and more detailed lies that are complete fabrication are easy to catch
Duping Delight - feeling happy when you get away with lying
- can result in micro-expressions of happiness while talking about sad shit
Interpersonal Deception Theory (Burgoon, 1996) - deceivers will look for indications that a receiver is suspicious
- receivers will look for indications that others are deceiving them
- detecting suspicions is easier and less socially costly than detecting lies
- calling someone out on their lies is socially costly and possibly inappropriate
- receivers show suspicion and the deceivers then modify their behavior to be less
suspicious
- the deceivers and receivers each modify their behavior based on the other
person's behavior
Data on How Difficult it is to Detect Deception - on average, people are 54% accurate in detecting lies
- most people have a ton of (misplaced) confidence in their lie-detecting abilities
- when CMC + high stakes, we suck at detecting deception cause they will take
more time to craft a believable lie
- on average, over CMCs, people are 8-20% accurate in detecting deception
Why We Suck At Lie-Detection 1) Competent Liars Alter Their Behavior
- they modify their behavior when detecting suspicion to lower that suspicion and
sell the lie
- "Counter-Measures"
2) No Pinocchio Nose
- there is no consistent, reliable behavior that we can look to to know that
someone is lying
3) Truth Bias
- we have an expectation that people close to us will be truthful to us
- that lets them lie easier to us
Counter-Measures - when liars match the posture and behaviors of the people they're lying to
- helps build rapport and sell the lie
, Curvilinear Curve of Detecting Deception - acquaintances are the best at lie detection
- people close to us give in to the truth bias
- people we don't know at all have no baseline for our behavior
- acquaintances are the best cause they have a baseline of our behavior but they
don't have truth bias
Types of Digital Deception 1) Identity-Based Deception
(i) Identity Concealment
- aspects of our identity are omitted or altered
- ex: presenting false age, lie about height and $ status
(ii) Identity Theft
- take someone else's identity and present it as our own
- ex: catfishing
(iii) Identity Forgery
- take lots of info from many sources to craft a brand new identity
- ex: spam, phishing, robocalls
2) Message-Based Deception
- lying about the content of our messages, also they know my real identity
- ex: "I got a flat tire" when I don't
3 Types of False Online Information 1) Fake News
- happens a lot now with AI
2) Rumors
- tabloids, lies in media
3) Fake Reviewers
- fake online reviews
- Astro-Turfing
Astroturfing - when you work for a business and give it a great online review
- pretend to be a customer
2 Types of Luring 1) Spamming
- not really nefarious
- ex: junk emails, spam emails
2) Phishing
- very nefarious/dangerous
- ex: trying to obtain sensitive info
- ex: bank info, passwords, SSI#
