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Transcript of Job Talk
Department of Telecommunications Personal Bio Sports Research Teaching Indiana University, Bloomington, IN
M.A. Telecommunications, (2008)
Ph.D. Telecommunications, Cognitive Psychology Minor Hobbies and interests Sports Evolutionary Psychology I became fascinated with the cognitive and social theoretical perspectives that evolution allows for
Cognitive psychology + evolutionary biology = EP
EP states that we (today’s humans) are left with the mental processes that best benefited our ancestors
Understanding how cognitive processes developed results in a more complete and thorough understanding of said processes
EP has been gaining popularity as an approach to studying human behavior, interaction, and cognition Violence Sex Social Media Examining the possible impact of mediated sports programming on racial stereotype formation. Weaver, A. J., Kobach, M. J., (2012) The relationship between selective exposure and the enjoyment of television violence. Aggressive Behavior, 38, 2, 175-184. Gender and empathy differences in negative reactions to both fictionalized and actual violent images. Kobach, M. J., Paul, B. M., A Multiple exposure approach studying cognitive and attitudinal effects of barely legal and clearly legal pornography Paul, B. M., Kobach, M. J. The male-female reactions to sexually explicit pornography: An empirical test of predictions of intra- and inter-gender differences Inter-gender differences in reactions to sexual and emotional infidelity within the context of Facebook. Is your Facebook profile saying what you think it is saying?
How people use Facebook information to determine if an individual makes a desirable potential long-term partner. Facebook friend requests from strangers:
Gender differences in mate access strategies on social networking sites. The social brain hypothesis approach to Facebook:
Determining what type of relationships are supplemented/intensified via Facebook interactions. If sports related media in anyway influences or is correlated with the perpetuation of these stereotypes then this is something that researchers, media consumers, media producers, and sports commentators must be made aware of. Faces of Whites and Blacks were used (common among similar IATs)
Subjects were instructed to hit either the ”e” or “i” key to categories words and faces
Instead of words that were some incarnation of GOOD or BAD, words that described either NATUAL ATHLETES or SMART ATHLETS were used. A unique IAT was designed specifically for this study using DirectRT. Key components included The Racial/Sports Fueled IAT The Implicit Association Test (IAT) To attribute African Americans’ athletic success solely on “natural” athletic ability trivializes all the effort and hard work that a particular individual has put into achieving his/her status in sports. Further, it diminishes the physical effort that is spent honing one’s body into the condition necessary for a professional athlete. How do we investigate this sensitive area of racial/sport stereotypes? The IAT was designed to measure the strength of associations between different social groups or objects and specific descriptive terms Natural Athlete
Perseverance Verses Furthermore, Whites are portrayed more commonly as natural leaders and more gracious in both victory and defeat in comparison to African American athletes. (Brillel, 1989; Jackson, 1989; McCarthy Rada, 1996; Rada, 2005; Whannel, 1992) Results indicate that athletic success achieved by:
African Americans is attributed to “natural” athleticism
Praise is usually limited too “god-given” abilities that center around strength,
size, speed and other related athletic traits
Whites is attributed to hard work and intelligence.
Praise often includes words and phrases like fortitude, intelligence, moral
character, strategic preparation, and coachability While African Americans have gained equality on the playing field, at times their accomplishments can be undermined by television’s biased coverage of sports. It is done in a very quick, subconscious way
It demands prompt pairing of various stimulus objects and traits
Decisions are made quickly (milliseconds), which forces the subject to rely on
associations that have been learned Is This Bad? These specific words were chosen based on their inclusion in previous mediated sports content analysis Previous Content Analysis Discussion This suggests that subjects who fell into the category of heavy sports viewers more easily associated pictures of Whites with ‘smart’ athlete words and pictures of Blacks with ‘natural’ athlete words when compared to the alternative. Additional analysis was run correlating the D scores with amount of time spent with different types of mediated sports. The mean latency difference for light mediated sports use was significantly different (F(1,111) = 8.98; p=.003) when compared to the mean latency difference for heavy sports use. Heavy mediated sports users: an automatic preference for Whites associated with ‘smart’ athlete words and Blacks associated with ‘natural’ athlete words was found (M difference = 151.51 ms; S.D. = 212.98; D = .71) suggesting a “strong” association. Light mediated sports users: an automatic preference for Whites associated with ‘smart’ athlete words and Blacks associated with ‘natural’ athlete words was found (M difference = 43.78 ms; S.D. = 167.39; D = .26) suggesting a “small” association. Overall: an automatic preference for Whites associated with ‘smart’ athlete words and Blacks associated with ‘natural’ athlete words was found (average IAT effect of M difference = 96.21 ms; S.D. = 197.62; D = .48), suggesting a “moderate” association. Determined
Big Smart athlete words: Natural athlete words: The mediated sports use survey that was designed specifically for this study (data for weekend mediated sports use was also collected). Sample screen shot of the IAT that was designed specifically for this study. European American or
Smart Athlete African American or
Natural Athlete A good deal of research has looked at how the athletic traits of White athletes are described in comparison to those of African American athletes in a mediated context. Mean Latency Difference in Milliseconds D Scores Results Subjects completed a mediated sports use survey and a
“mediated sports-stereotypes specific” IAT Overview Participants
114 undergraduates participated
Subjects were given a brief overview of the media use survey and the IAT and then were seated individually at a laptop computer. Subjects first completed the media use survey and then contacted the researcher to initiate the IAT.
IAT: The mean latency for African American/Natural Athlete and European American/ Smart Athlete (“compatible” responses) was subtracted from the mean latency for African American/Smart Athlete and European American/Natural Athlete (“incompatible” responses). Positive difference scores indicate stronger associations with consistent pairings compared to inconsistent pairings. The mean latency scores were converted into D scores. This results in scores that range from 0 to 1, with larger numbers indicating stronger associations and small numbers indicating smaller associations.
Mediated sports use survey: Subjects’ total weekly time spent with mediated sports was determined and then divided into light and heavy users based on a median split of their overall total time spent with mediated sports use for additional analysis. Study Design Matthew Kobach
Indiana University Examining The Possible Impact of Mediated Sports
Programming on Racial Stereotype Formation Data Collection and Preparation Prepared These findings suggest that if an image is violent/gory/unpleasant females do not emotionally distinguish between real and fake. Fake images illicit similar emotional responses as real images.
Males seemed to not be as bothered when they thought they were looking at fake images. Males seemed better able to repress emotional related responses when they were viewing fake images. It’s as if males, in some sense, can ‘look the other way’ to the blatant violence if it is fake, whereas females cannot or choose not to.
This information helps shed some light on why males’ consumption of violent media outweighs females consumption of similar media. Interpretation Males rated the real images significantly more negatively (M= 5.79, SE=.141) compared to the fake images (M= 4.88, SE=.128) at the .05 level.
Males also rated the fake images more positive (M= 1.96, SE=.083) than the real images (M= 1.67, SE=.091), (however, not nearly to the same extent as the negative scores).
There is a very apparent difference between males emotional responses to “real” and “fake” images. Males This data suggests that females rate what they thought were fake images (M= 6.06, SE=.142) almost as negatively compared to the images they thought were real (M= 6.10, SE=.136).
Similar results for females are found when the positive scores are examined for the fake images (M= 1.52, SE=.092) compared to the real images (M= 1.44, SE=.088).
The difference between the two conditions is so small, it is as if almost no difference exists at all.
1 = Not at all negative/positive
7 = Extremely negative/positive The graphs represent the means of each condition. Hypotheses --Males’ positive score for the fake images will be higher than the
real condition and the negative score for the fake images will be
lower than the real condition --Males’ positive score will be higher than females’ positive score and
males’ negative score will be lower than females’ negative score. Because 1) physiological gender differences exist in emotional processing, 2) males are more likely to consume violent media when compared to females, and 3) both males and females respond differently to real images when compared to fake images, differences in self-report data are predicted, leading to the following hypotheses: Groups viewed unpleasant images (mutilations) and were told to keep in mind that all of the images were either real, with violent scenes from different cultures or fake (stage make-up), and were used for cinematic purposes. Participants in the fake condition rated the experience less unpleasant than those in the real condition (Oliveira, 2003). Research indicates that in males specifically (both children and adults), there is a
positive correlation among selective exposure and an indication of violence
(Bushman Bushman Cantor & Harrison, 1997).
Males place significantly more importance on violence when compared to females
(Valkenburg and Janssen (1999).
Males are significantly more likely to have reported viewing as least one “extremely
violent” movie when compared to females (Sargent et al., 2002).
Males spend more time on video games than females (Rideout, Vandewater, & Wartella, 2003).
55% of gamers are male genres (Entertainment Software Association’s report,
-The shooters genre is the third best-selling computer game genre in the U.S.
consisting of 16.3% of the population of game players. Differences in viewing “real” or “fake” images Gender differences in violent media consumption This study is a 2 (Gender) X 2 (Condition: Real
or Fake) design. All are between subject factors Male and female subjects use different set of neural correlates when processing
mediated faces showing either happy or sad expressions (Lee et al., 2002).
Identical visual stimuli elicit different levels of arousal and valence in men and
women. Stronger brain activation in women for affectively negative pictures
was observed in the anterior and medial cingulate gyrus (Wrase et al., 2003).
Event-related potentials (ERPs) data suggests that pleasant and unpleasant visual
stimuli activated different neuronal structures in women compared to men
(Campanella et al., 2004).
Examinations of brain maps of men and women as they view pictures of varying
arousal and neutral content suggests that men and women respond differently
to highly aversive pictures (Flaisch et al., 2003). Gender differences in physiological responses Brief Discussion Results Two ANOVAs were conducted to evaluate the real/fake condition (real or fake) and gender (male or female) for both positive scores and negative scores. Negative Scores
Real/Fake condition: F(1, 179) = 10.27, p = .001
Gender: F(1,179) = 25.259 p < .0001
Interaction: F(1, 179) = 9.96, p = .002 M= 6.06
SE=.142 M= 1.96
SE=.083 M= 1.67
SE=.091 M= 1.52
SE=.092 M= 1.44
SE=.088 M= 4.88
SE=.128 M= 6.10
SE=..136 M= 5.79
SE=.141 You will now be shown multiple unpleasant images. Many of these images depict violent acts, or are the result of violent acts, and are from all around the world.
Your task when responding to these questions is to keep in mind that these images are REAL.
Please rate BOTH how positive and how negative each picture made you feel. Stage make-up, Photoshop, and similar techniques have given cinema producers the ability to create very realistic images that are in no way real. This is a study to determine individual's emotional responses to realistic, yet FAKE unpleasant images (think crime scene images from television programs such as Law and Order, CSI, Bones, etc.).
Your task when looking at these images is to keep in mind that they are all FAKE, and were originally created for cinematic purposes from around the world.
Please rate BOTH how positive and how negative each picture made you feel. Negative Scores Positive Scores Fake Condition Real Condition Independent Variable
Emotional Positive Valence measured by a
7-point Likert scale for “real” or “fake” images
Emotional Negative Valence measured by a
7-point Likert scale for “real” or “fake” images Overview Positive Scores
Real/Fake condition: F(1, 179) = 4.28, p = .04
Gender: F(1, 179) = 13.82 p < .0001
A significant interaction was not found The primary goal in this study was to investigate two different topics that have been examined separately in the past:
The first topic is the differences in gender in relation to valence toward mediated
images (often violent images). Further, special consideration was given to males’
consumption of this media compared to females.
The second topic is people’s valences toward unpleasant (violent/gory) images that
they were told were either real or fake (stage make-up, Photoshop).
This study combined these two topics into one larger topic. Participants
183 undergraduates (46 in the real/female cell, 42 in the fake/female cell, 43 in the
real/male cell and 52 in the fake/male cell), participated in this study.
Each participant completed the experiment individually online. They were randomly assigned
to either the “real” or “fake” condition. Both conditions began with a series of demographic
and similar questions. Next, using a 7-point Likert scale, they rated both how positive and
how negative the images they were exposed to made them feel. Other than the copyright logo
added to most of the images in the “fake” condition, the images were identical.
An average positive and negative score across all images was determined for each participant. Study Design
Sample Image and instructions Matthew Kobach
Indiana University Females Gender Differences in Valence Towards “Real”
and “Fake” Unpleasant Images Findings in Earlier Studies Data Collection and Preparation
Images were carefully selected from IAPS based on their unpleasant/violent/gory nature and their believability to be perceived as both “real” and “fake.”
To assure the images in the ‘fake’ condition were indeed perceived as fake certain precautions were taken:
Copyright logos were added to most of the “fake” condition images
Participants were told repeatedly that the images were manipulated with Photoshop or
Images were pre-tested to determine if any images were problematic (e.g. too graphic). **Paper presented at the annual meeting of the International Communication Association, Chicago, IL, USA (2009) **Paper presented at the annual meeting of the International Communication Association, Chicago, IL, USA (May, 2009) We must explore how these innate mechanisms work in conjunction with our current modern environment (the media)
Our minds were not developed for media consumption
We process mediated information the same way they process non-mediated information
We treat media similarly to how we treat people
We use modern technology to satisfy ancient needs
If we know how people will respond to people, we know how people will respond to media “Psychology
will be based on a new
foundation, that of the
necessary acquirements of
each mental power”
-(Darwin, 1859). how this relates to mass communication Thus, we need to ask...... What cognitive mechanisms where beneficial in ancestral times?
What environmental cues activate these processes?
How do these processes guide thoughts, feelings, and behavior?
How do these cognitive mechanisms function in today’s social and mediated world?
How do these evolved social mechanisms function in a mediated context? To understand media consumption, we must understand our evolved
cognitive functions from an evolutionary psychological perspective **Paper presented at the annual meeting of the National Communication Association, Chicago, IL, USA (November, 2007) Brand new technology, same old brains:
How evolved cognition influences
Facebook user behavior Kobach, M. J. (2009-Current) Co-Investigator, Assessment of Vibration and Sexual Pleasure. Church & Dwight, Co., Inc., $32,000.00
Assessed vibration and sexual pleasure for the Trojan company
Responsibilities: Created content, designed protocol, created several MediaLab programs, cleaned and coded data, recorded physiological data, and the writing process involved throughout. Fizziology uses real-time social media information to provide meaningful business insights by monitoring social media buzz from Facebook, Twitter and blogs. I am trained to accurately code sentiment, statistically analyze data, spot trends, assist in predictive equation development, and to understand the worlds of both entertainment and social media. Social Media Analyst
at Fizziology (2011-Current) Research Grant **Paper presented at the annual meeting of the International Communication Association, Chicago, IL, USA (May, 2009) **Paper accepted at the annual meeting of the National Communication Association, Orlando FL, USA (November, 2012) Results Social The goal of this course was to deepen the
understanding of the complicated relationship
between media, people, and societal institutions.
I created the entire class content
(i.e., exams, syllabus, lectures, power points, assignments)
I coordinated the associate instructors responsibilities
I developed a unique grading rubric Led weekly discussions
created unique discussion content
intermediary for the instructor and the students
helped develop lecture content Examining the possible impact of mediated sports programming on racial stereotype formation (2009)
Gender differences in valence in "real" and "fake" violent images (2009)
The effects of exposure to pornographic depictions featuring youthful-looking females on viewer cognitions and attitudes (2009)
Cross Unit Panelist-- Keywords in Communication: Evolution. (2009)
Sounds like a winner: examining structural features and basic content in five years of award-winning radio ads (2006) The Male-Female Reactions to Sexually Explicit Pornography: An Empirical Test of Predictions of Intra- and Inter-gender Differences (2012)
Selective exposure and the enjoyment of media violence: Connecting the dots (2007) Being born in Wisconsin, I
was raised a Green Bay Packer fan I also played several sports
growing up This passion sparked my initial
interest in media effects, and is
the reason I chose this career path This led to the development of
my master's thesis I also am very interested in
how people interact socially When I finished my thesis, social media
had really began to take off, and it soon
became my academic interest Because it was an emerging area,
it was difficult to find people in my
department who shared my passion This lead to my current (somewhat)
self-guided exploration of how
humans use social media to extend
(or limit) their social reach But how should I
this issue? What I can offer your school: Someone who understands the changing mediated environment, and enjoys exploring what social media has to offer A researcher with a strong theoretical background who will continue along this line of research A teacher with an extensive teaching background because I was giving the opportunity to lead and create content for three discussions every week. A motivated teacher who wants to create a unique, engaging, and thought provoking learning environment A researcher who understands the process involved in grant procurement