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PAD 637: Lecture

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Title: PAD 637: Lecture


1
PAD 637 Lecture 4 Data Collection and
Social Cognition 09/29/04 Rinata Shamshetdinova
2
Techniques for social data collection/1
  • questionnaires
  • roster vs. free call
  • free vs. fixed choice
  • ratings vs. complete ranking
  • interviews
  • face-to-face
  • telephone
  • observations
  • Planting an observer in a room
  • Random appearance, each time over a limited period

1
3
Techniques for social data collection/2
  • archival records
  • structured data sets
  • unstructured data sets (coding required)
  • experiments
  • planting rumors
  • small world
  • others
  • social cognitive structures
  • ego-centered
  • small world
  • diary

2
4
Boundary Specifications Sampling
  • 2 approaches to boundary definition
  • Nominalist approach analyst self-consciously
    imposes a conceptual framework constructed to
    serve his or her own analytic purposes.
  • Realist approach the boundaries of the social
    entities are defined by actors themselves. Social
    entity exists as a collectively shared subjective
    awareness of all, or at least most, of the
    actors.
  • Sampling
  • Relevant sampling units?
  • Estimation of network properties based on
    sampling units
  • Snowball network sample

3
5
Information accuracy
  • technical aspect - the accuracy of data
    collection
  • What data do we need?
  • cognitive aspect the accuracy of informants
  • Krackhardt behavioral measures of interaction
    are not very closely related to participants
    self reports of the same interactions often
    recall is being used as a surrogate of behavior.
  • Bernard, Killworth and Sailer about 52 of what
    informants said was wrong.
  • Freeman, Freeman and Romney people's recall of
    their interactions with others is systematically
    biased toward what is normal and/or logical
    recalling important people more then others.

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6
Cognitive Social Structures
  • CSS
  • sender
  • receiver
  • perceiver
  • Rijk person k thinks that person i approaches
    person j for help and advise
  • Characteristics
  • Amount of information in CSS gt that in
    traditional SS ? problems in data collection
  • No assumption is made about the perceptions
    being correlated with each other.

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Useful bits/1
  • Informants who usually kept records of their
    behavior were not more accurate than those who
    did not. (BKS)
  • Slightly obtrusive observation has no noticeable
    effect on informant accuracy. (BKS)
  • Telling people in a group that they are expected
    to get more accurate in repeated experiments over
    time produces no significant improvement in
    accuracy of reporting communications. (BKS)
  • Asking people who do you like? produces about
    the same answers as asking them who do you talk
    to? (BKS)
  • Asking people about the significance or
    importance of their interactions with others is
    of little use, since it produces no better
    results than simply asking them who they talked
    to. (BKS)

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Useful bits/2
  • In general, the more recent the time of the
    window over which informants report their
    communication, the more accurate they tend to be.
    However, only 6 of informant accuracy can be
    accounted for by this factor. (BKS)
  • Over all data sets, people can recall or predict
    less than half of their communications, measured
    either on amount or on frequency. (BKS)
  • For publicly available information there was
    both agreement and accuracy. For questions where
    the answers were not public, there was very
    little agreement, and hence high inaccuracy.
    (Young Young)
  • People represent enduring patterns of
    interaction more accurately then individual
    instances of behavior (FR)

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Question 1
  • Does agreement presupposes accuracy, especially
    when we deal with a closely-knit network? Under
    what conditions would it be true?

8
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Question 2
  • Accuracy vs. problems in data collection and
    treatment should we, at this stage use Cognitive
    Social Structures in our Empirical Exercises?

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Question 3
  • Under what circumstances can random sampling be
    used???

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