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- PHILIPP MASUR -
SUMMARY OF ARTICLES&LECTURES
New Media Challenges ‘22
FOCUS: Social Media: Characteristics, business models and persuasion
MAIN SUBJECTS:
● Social Media and the Network Economy
● What are the characteristics of social media and e-commerce environments?
● How did platforms (like Google and Facebook) become so central?
● Why do some platforms grow huge, while others fail?
● eProfiling & ePersuasion
● What kind of information do websites collect about you?
● How do they use this information to persuade you?
● Social Contagion on social media
● How do behaviors, attitudes, or emotions spread across networks?
● How do social media support contagion effects?
● What can we do to counteract potentially negative network effects?
● Media Literacy Digital Citizenship
● What kind of information do websites collect about you?
● How do they use this information to persuade you?
WEEK 3 - LECTURES 6,7,8 2
LECTURE 7: A Network Economy: Online Business Models in the Age of Information (Philipp
Masur)
The like economy Social buttons and the data-intensive web. New media & society - Gerlitz, C., &
Helmond, A. (2013)
Is the Internet driving competition or market monopolization. International Economics and
Economic Policy - Haucap, J., & Heimeshoff, U. (2014) 2
LECTURE 8: eProfiling and ePersuasion (Philipp Masur)
Private traits and attributes are predictable from digital records of human behavior - Kosinski, M.,
Stillwell, D., & Graepel, T. (2013)
Information systems research - Wright, R. T., Jensen, M. L., Thatcher, J. B., Dinger, M., & Marett,
K. (2014)
Personalizing persuasive technologies Explicit and implicit personalization using persuasion
profiles - Kaptein, M., Markopoulos, P., De Ruyter, B., & Aarts, E. (2015) 8
WEEK 4 - LECTURES 9,10 17
LECTURE 9: Social contagion on social media: How behaviors may spread across online
networks (Philipp Masur)
Social norms A review. Review of Communication Research - Chung, A., & Rimal, R. N. (2016)
Behavioral Contagion on Social Media Effects of Social Norms, Design Interventions, and Critical
Media Literacy on Self-Disclosure - Masur, P. K., DiFranzo, D. J., & Bazarova, N. N. (2021). 17
LECTURE 10: Media literacy and digital citizenship (Philipp Masur)
Developing social media literacy How children learn to interpret risky opportunities on social
network sites. Communications - Livingstone, S. (2014)
Introducing the Social Media Literacy (SMILE) model with the case of the positivity bias on social
media. Journal of Children and Media - Schreurs, L. & Vandenbosch, L. (2020) 21
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WEEK 3 - LECTURES 6,7,8
LECTURE 7: A Network Economy: Online Business Models in the Age of Information (Philipp
Masur)
The like economy Social buttons and the data-intensive web. New media & society - Gerlitz, C., &
Helmond, A. (2013)
Is the Internet driving competition or market monopolization. International Economics and Economic
Policy - Haucap, J., & Heimeshoff, U. (2014)
This lecture:
- Why do we call it the network economy and the age of information?
- What are the characteristics of social media and e-commerce environments?
- Why do some platforms grow huge, while others fail?
Introduction: The Age of Information
In the last century, we moved from a more industrial-focused society towards a more
information-based society. Value is not only generated by (selling) primarily goods, but also by using
information.
*See Youtube: ‘Networked economy explained’
Traditional societies (perhaps 30 years ago, without the internet) were primarily based on on economy
that was based on goods. It was constrained by physical means. In order to get your product to the
people/consumers, it had to be made, shipped, packaged etc etc. A much slower process vs now.
Today, this is no longer the case, because of the internet. Businesses are being run out of garages.
You do not need big factories and/or offices before you can grow your company and bring your
product out to the people. It starts by setting up a website (look at Google and Facebook founders,
they started from their garage (Google/Apple) or their dorm (Facebook)), but became hugely
influential because they saw early on that information can be used as a commodity. A value that can
be traded and sold. They use the information to sell it but also to provide a service.
Networks, Networks, Networks
Example/Question: How many ‘hands’ separate you from Donald Trump?
Stanley Milgram, (1967): ‘The simplest way of formulating the small-world problem is: starting with any
two people in the world, what is the probability that they will know each other? A somewhat more
sophisticated formulation, however, takes account of the fact that while person X and Z may not know
each other, they share a mutual acquaintance’’
A simple experiment was conducted: (The theory of ‘Its a small world’)
+ a package needs to go from a random person A to a random person B
+ person A can only send the package to acquaintances
+ acquaintance is asked to do the same as person A
Findings:
+ How many steps separate A and B? –? Between 5 and 7.
→ ‘it’s a small world’
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Dodds, Muhamad & Watts (2003) conducted an experimental study of search in global social
networks → 60.000 e-mail users attempted to reach one of 18 targets in 13 countries by forwarding
messages to acquaintances. On average it took them 5-7 steps.
Other examples of networks:
- Neurons are organized in networks
- Streets and roads are networks
- Languages
- Networks of people (Instagram users’ network of followers)
Networks are the basis for the internet networked economy
Communication and information technology is based on networks
We can differentiate various types of networks:
- Hardware/computer networks (the internet)
- Hyperlink networks (the web)
- Social networks (Facebook, Twitter, Instagram..)
→ Friends
→ Interactions
→ Like/share/retweet networks
- Information Networks
→ Semantic
→ Structural
Networks - Terminology
Understanding network theory and network characteristics can be a big advantage in the network
economy → successful companies (Google, Facebook, Amazon, Apple) use network analysis to
make money.
Type of Network Models:
- UNIMODAL (simple) graph
- MULTIPLE (valued) graph
- (A)SYMMETRIC graph
- BYPARTITE graph
Network measures:
- Degree (tells us something about the
importance of a node → in the
Unimodal you can see that B had 2
connections and can thus be seen
as the most important)
- Degrees of separation, distance, or
path length (Milgram, the number of
paths between A to B and A to C for
example)
- Centrality (the number of degrees of
separation : overall number of nodes
(-1), this per ‘central, A, B, C’)
- Status (a position of a node in a
network → powerful, important,
respected?)
- Cliques
