08-newcomers-socialization-v4x - Social Web 2012 (Fall)

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13 Δεκ 2013 (πριν από 3 χρόνια και 10 μήνες)

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Socializing Newcomers

Previously


Contributions


Intrinsic, extrinsic, social motivations


Wisdom of Crowds


Ways of aggregating knowledge from lots of people


Voting schemes, prediction markets


Crowdsourcing


DARPA red balloon,
Soylent


Technical aspects


Visualizations and the Social Web


Design principles



This Week


Some challenges
when dealing with newcomers


Some relevant theory


Theories of socialization from small group psychology

and organizational
behavior


Theories of selection & signaling/screening


Review some empirical research & designs showing
some of the variation in socializing newbies


Python


Wikipedia


Some design questions & design claims


Resources available


Sandbox
vs

full integration


FAQ
vs

Welcoming committee


Lurking
vs

training

Newcomers
Both
a Resource

& Source of
Problems


A steady supply of newcomers
crucial
to continued
success of an online
community


But
newbies often
present
problems. Examples?


Don’t know how the group works


screw
-
up



require
training/education/socialization


Have less to contribute & need more support



effort sink


threaten old
-
timers


Investigating


little motivation to contribute


Different
knowledge


threats and/or source of change


Not aligned


may be
malicious


Untrustworthy until proven or
familiar

Problems of Newcomers in Online Communities


Recruiting


~70%
SourceForge


projects
have no

active members


Only
22% of newly

registered
project

attract
even one

additional members

Problems of Newcomers in Online Communities


Early
commitment


In Perl open source project, 54% of people who

register
to participate never contribute


25% of vetted registrants in Cancer Support
Community groups leave before participating


90% of registrants in Second Life leave after first
session


Median Wikipedia editor contributes for only one
day

Problems of Newcomers in Online Communities


Inappropriate
behavior


In Wikipedia, newcomers are 3 times more likely to
have edits reverted than experienced editors, probably
because content is of lower quality.


In Usenet discussion groups, newcomers questions
answered less
.

Every Successful Online Communities Needs to Solve
Problems of Dealing with Newcomers


Recruiting a supply


Who are we looking for?


How do we attract them to join?


Assessing their value & trustworthiness


Who should we recruit?


Who should we try to keep?


Whose contributions should we value?


Keeping them around & developing their commitment


How do we get the valuable ones to stick around, contribute,

and proselytize for us?



Training them to be “one of us”


How do we show them/teach them what we are?


How do we get them to behave appropriately?


Keeping their ignorance or ill
-
will from causing trouble



Importance of challenges vary with community

Why Dealing with Newcomers Is Hard


All especially hard, because newcomers often:


Drive
-
by



can’t deliver your message


Uncommitted




leave easily


Historyless




don’t know if you can trust them


Clueless



may act inappropriately


Different




make things uncomfortable for old
-
timers



Unconnected



few levers for control


Research on socialization of newcomers in
organizations is relevant

Recruiting

Diffusion of
Innovation Predictable











S
-
shaped diffusion curve


Shape differs across innovations: speed & asymptote


Phone: 60 years to reach 50% household penetration & asymptotes at 93%


Radio: 10 years to reach 50% household penetration & asymptotes at 99%


TV: 9 years to reach 50% household penetration & asymptotes at 98%


VCR: 6 years to reach 50% household penetration & asymptotes at 84%

Facebook Growth

Diffusion
both economically
rational

and
a social process


Innovation attributes


Adoption based on a cost
-
benefit trade
-
offs


Benefits


Improvements in task performance


Improvements in quality of life


Costs


Financial


Transactional


Costs & benefits change over time


E.g., Externalities


Adoption based on social influence


Rogers: Diffusion of Innovation Model


Most diffusion occurs
through communication


Mass media strong early on


Especially important for
raising awareness of
innovation


Interpersonal
communication more
important overall


Influence of interpersonal
communication grows


Especially important for
persuasion to adopt


Importance of social
networks

Diffusion as
Communication


S
t

=

p




Remaining

+

q



Adopters







Potential


Remaining Potential




External/Innovation

Internal/Imitation











where
:


S
t



=

sales
at time
t


p



=


coefficient of innovation” (mass media + other external influence)


q



=


coefficient of imitation” (word of mouth influence)


# Adopters

=
S
0

+
S
1

+ • • • +
S
t

1


Remaining

=

Total
Potential


# current adopters

Mahajan
,
V.
,
Muller
,
E.
, &
Bass
,
F. M.

(1990).
New product diffusion models
in marketing: A review and directions for research.

Journal of Marketing
,
54
(1),
1
-
26
.

Predicating Diffusion Rates

(The Bass Diffusion Model)

Technical Specification

of the Bass Model

The Bass model proposes that likelihood of adapting at time t (
L
(
t
) )

is
a
linear function
:






q





L
(
t
) =
p

+

––

N
(
t
)

(2)






N

where


p

=

Coefficient of innovation (or coefficient of external influence)


q

=

Coefficient of imitation (or coefficient of internal influence)


N
(
t
)

=

Total number of adopters of the product up to time
t


N

=

Total number of potential buyers of the new product

Then the number of customers who will purchase the product at time
t

is equal
to
Nf
(
t
) . From (1), it then follows that:






q





Nf
(
t
) = [
p

+

––

N
(
t
)][1


N
(
t
)]

(3)






N

Nf
(
t
) may be interpreted as the number of buyers of the product at time
t

[

=

(
t
)].
Likewise,
NF(t

) is equal to the cumulative number of buyers of the product up
to time
t

[

=

N
(
t
)].

Example Use of Mass Media

Other Examples

Interpersonal Communication

Facebook Examples?


Examples

Facebook Examples?


Frictionless sharing


Anytime you're reading news from a social news app or
listening to music from a social music app, Facebook
automatically shares it to your Facebook profile



Innovation

Imitation


Product/

parameter


parameter



Technology

(
p
)

(
q
)

B&W TV

0.028

0.25

Color TV

0.005

0.84

Air conditioners

0.010

0.42

Clothes dryers

0.017

0.36

Water softeners

0.018

0.30

Record players

0.025

0.65

Cellular telephones

0.004

1.76

Steam irons

0.029

0.33

Motels


0.007

0.36

McDonalds fast food

0.018

0.54

Hybrid corn

0.039

1.01

Electric blankets

0.006

0.24

A study by Sultan, Farley, and Lehmann in 1990 suggests
an average value of 0.03 for
p

and an average value of
0.38 for
q
.

Parameters of the Bass Model in

Several
Product Categories

Anything else going on in online
communities to influence adoption?


Does the Bass model accurately describe your
experiences?


Ex. Why you joined Facebook / Twitter /
Reddit

/
etc
?

Selection: How do you get the new
members you want?

Some Design Choices


In open source software, newcomers aren’t trusted
until they prove themselves through technical
discussion, bug reports & patches


But in Wikipedia, even anonymous newcomers

are given the right to edit most articles



Why this difference in socialization practices?



When do you choose one
vs

the other?



Rational
for Groups to be Skeptical of
Newcomers


In many communities, newcomers
a
burden or threat


Many newcomers
request help,
conversation,
or
membership from existing members


Existing members can’t respond to every overture


Existing members may be suspicious of newcomers


In Wikipedia, newcomers & anonymous editors are
more likely to vandalize or offer poor content


More senior editors disproportionately revert

their work

Rational
for Groups to be Skeptical of
Newcomers


Group
is more likely to be welcoming if they perceive
newcomers as “deserving”


If newcomers signal their legitimacy and prior
investment in the group, existing group members may
pay them more attention


Newcomers’ actions & language provides a basis for
evaluation



Thesis: Individuals may use self
-
revealing
introductions to signal both legitimacy & investment

Newcomers Not Trusted

(van Maanen & Schein)

Don’t Bite the Newbies


Wikipedia: Newcomers more likely to be reverted

(& they are more likely to leave when reverted)



Is this good?

Halfaker
, A.,
Kittur
, A., &
Riedl
., J. (2011). Don't bite the newbies: How Reverts
affect the quantity and quality of Wikipedia work.
WikiSym

2011: Proceedings
of the 5th International Symposium on Wikis and Open Collaboration (pp. 1
-
10). NY: ACM.

Reprise: Newcomers are distrusted

0
0.2
0.4
0.6
0.8
Hobby
Political
Support
Technical
Group type
Probability of Getting a Reply
Newcomers
Old-timers

Political discussion and hobby groups are especially
likely to ignore first
-
time posters & acknowledge old
-
timers

Groups Respond Less to Newcomers

The Value of Reputation on eBay: A Controlled
Experiment


Compare sales & price of matched
lots of postcards


Established seller (2000
transactions w/ only one negative


vs. new seller with no reputation



Guesses as to results?

The Value of Reputation on eBay: A Controlled
Experiment


Compare sales & price of matched
lots of postcards


Established seller (2000
transactions w/ only one negative


vs. new seller with no reputation



Guesses as to results?


Established seller more

likely
to complete sale

(
63% vs. 56%, p < .07)


Established seller gets

~
8% more per sale