1. New Media Research Methods
Week 2

2. OUTLINE: Overview of social science research Social research design
Data analysis

3. Overview (1): Social research design

4. The Foundations of Social Science
Two pillars of science:
Logic
Making sense
Theory
Observation
Corresponding with what we observe
Data Collection & Analysis

5. Social Science = Theory + Data Collection + Data Analysis

6. Theory, Not Philosophy or Belief
Social theory has to do with what is, not with what should be.
Theory – A systematic explanation for the observations that relate to a particular aspect of life.
Social science can help us know what is and why.

7. Aggregates, Not Individuals
The collective actions and situations of many individuals.
Focus of social science is to explain why aggregated patterns of behavior are regular even when individuals change over time.

8. Concepts and Variables
Concept – An agreement about what a term means.
E.g., beauty
Variables – Logical groupings of attributes.
Not constant
E.g., the symmetry level of a human face
Attributes – Characteristics or qualities that describe an object.
Beautiful, neutral, ugly…

9. vs.
Legolas
Gollum

11. Independent Variable – A variable with values that are not problematical in an analysis but are taken as simply given.
Dependent Variable – A variable assumed to depend on or be caused by another.
E.g., beauty  income
income  beauty?

12. Some Dialectics of Social Research
Idiographic and Nomothetic Explanation
Idiographic – An approach to explanation in which we seek to exhaust the idiosyncratic causes of a particular condition of event.
Nomothetic – An approach to explanation in which we seek to identify a few causal factors that generally impact a class of conditions of event.

13. Qualitative and Quantitative Data
Qualitative Data – non-numerical data
Quantitative Data – numerical data

14. Pure and Applied Research
Pure Research – Gaining “knowledge for knowledge’s sake.”
Applied Research – Putting research into practice.

15. Inductive and Deductive Theory
Induction – The logical model in which general principles are developed from specific observations.
Deduction – The logical model in which specific expectations of hypotheses are developed on the basis of general principles.

16. The Traditional Model of Science
Theory
To derive hypotheses which can be tested
Operationalization – Developing operational definitions, or specifying the exact operations involved in measuring a variable.
Operational Definition – The concrete and specific definition of something in terms of the operations by which observations are to be categorized.
Observation – Specifying the exact operations involved in measuring a variable.

18. Two Logical Systems, Revisited
Deductive and Inductive Reasoning
Deductive = Traditional Model of Science
Syllogism

19. Deductive Theory Construction
Specify the topic.
Specify the range of phenomena your theory addresses.
Identify and specify your major concepts and variables.
Find out what is known about the relationships among those variables.
Reason logically from those propositions to the specific topic you are examining.

20. Inductive Theory Construction
Observing aspects of social life and seeking to discover patterns that may point to relatively universal principles.
Grounded Theory
Field Research: the direct
observation of events in progress

21. The Links Between Theory and Research
Deductive Model – research is used to test theories.
Inductive Model – theories are developed from analysis of data.

22. The Wheel of Science

23. The Purposes of Social Research
Mapping out a topic that may warrant further study later (exploratory)
Describing the state of social affairs (descriptive)
Providing reasons for phenomena, in terms of causal relationships (explanatory)

24. Three Purposes of Research
Exploration
To satisfy the researcher’s curiosity and desire for better understanding
To test the feasibility of undertaking a more extensive study
To develop the methods to be employed in any subsequent study

25. Description
Describe situations and events through scientific observation

26. The three purposes can co-exist in the same study.
Explanation
Descriptive studies answer questions of what, where, when, and how
Explanatory studies answer questions of why
The three purposes can co-exist in the same study.

27. The Logic of Nomothetic Explanation
Goal: to find a few factors that can account for many of the variations in a given phenomenon.

28. Criteria for Nomothetic Causality
The variables must be correlated
Correlation – An empirical relationship between two variables such that changes in one are associated with changes in the other, or particular attributes in one are associated with particular attributes in the other.
The cause takes place before the effect
The variables are nonspurious
Spurious Relationship – A coincidental statistical correlation between two variables shown to be caused by some third variable

29. ?

31. Music that makes you dumb

33. Units of Analysis The what or whom being studied.
E.g., “Twenty-four percent of the families have more than one adult earning $10,000 or more.”

34. Individuals Groups Organizations
Students, voters, parents, children, Catholics
Most common unit of analysis for social research
Groups
Gang members, families, married couples, friendship groups
Organizations
Corporations, social organizations, colleges

35. Social Interactions Social Artifacts
Telephone calls, dances, online chat rooms, fights
Social Artifacts
Social Artifact – any product of social beings or their behavior.

36. Faulty Reasoning about Units of Analysis
The Ecological Fallacy – erroneously drawing conclusions about individuals solely from the observations of groups.
SMD vs. SE; female vs. male
Reductionism – a strict limitation (reduction) of the kinds of concepts to be considered relevant to the phenomenon under study.
NBA winner vs. loser teams; individual players

37. The Time Dimension
Cross-Sectional Study – A study based on observations representing a single point in time, a cross section of a population.

38. Longitudinal Study – A study design involving the collection of data at different points in time.
Trend Study – A study in which a given characteristic of some population is monitored over time.
Economy Growth vs. depression level
Cohort Study – A study in which some specific subpopulation, or cohort, is studied over time.
Panel Study – A study in which data are collected from the same set of people at several points in time.

39. A Cohort Study Design

40. Comparing Types of Longitudinal Studies, Example: Depression level
Trend Study – looks at shifts in depression level over time.
Cohort Study – follows shifts in depression level among those born in the 1980s & 1990s.
Panel Study – follows the shifts in depression level among a specific group of people over time.

41. Approximating Longitudinal Studies
Researchers can draw approximate conclusions about longitudinal processes even when cross-sectional data are available.
Imply processes over time
Make logical inferences
Ask individuals to recall past behavior
Cohort analysis

42. How to design a research project?

44. Define the purpose of your project – exploratory, descriptive, or explanatory?
Specify the meanings of each concept you want to study
Select a research method
Determine how you will measure the results

45. Determine whom or what to study
Collect empirical data
Process the data
Analyze the data
Report your findings

46. The Research Proposal Elements of a Research Proposal
Problem or Objective
Literature Review
Subjects for Study
Measurement
Data Collection Methods
Analysis
Schedule
Budget
(Institutional Review Board)

47. Overview (2): Analysis - Measurement

48. To test a hypothesis: Specify variables you think are related
Specify measurement of variables
Hypothesize correlation, strength of relationship, statistical significance
Specify tests for spuriousness

49. Framing a hypothesis: Principles: Testable Clear
Example 1: Age is related to attitudes toward women’s liberation.
Example 2: Age is related to attitudes toward women’s liberation, with younger adults being more supportive than older adults.
Example 3: Age is negatively related to attitudes toward women’s liberation.

50. Measuring Anything that Exists
Measurement – Careful, deliberate observations of the real world for the purpose of describing objects and events in terms of the attributes composing the variable.
How would you measure…
age?
grade?
satisfaction with SJTU?

51. Conceptions, Concepts, and Reality
Conceptualization – The mental process whereby fuzzy and imprecise notions (concepts) are made more specific and precise.

52. Kaplan (1964): Three classes of things that scientists measure
Direct observables, e.g., color
Indirect observables, e.g., gender in a questionnaire
Constructs, e.g., IQ
Concepts as Constructs
Concepts are constructs derived by mutual agreement from mental images.
Conceptions summarize collections of seemingly related observations and experiences.

53. Conceptualization
Conceptualization – The process through which we specify what we mean when we use particular terms in research.
We cannot meaningfully answer a question without a working agreement about the meaning of the outcome.
Conceptualization processes a specific agreed-on meaning for a concept for the purposes of research.

54. Indicators and Dimensions
Indicator – An observation that we choose to consider as a reflection of a variable we wish to study.
Violent behaviors
Dimension – A specifiable aspect of a concept.
Physical violence vs. Verbal violence

55. Identify appropriate indicators and dimensions for…
Poverty
Charisma

56. The Interchangeability of Indicators
If several different indicators all represent the same concept, all of them will behave the same way the concept would behave if it were real and could be observed.

57. Real, Nominal, and Operational Definitions
A nominal definition is one that is simply assigned to a term without any claim that the definition represents a “real” entity.
Beauty is a characteristic of an animal, idea, object, person or place that provides a perceptual experience of pleasure or satisfaction.
An operational definition specifies precisely how a concept will be measured – that is, the operations we will perform.
Beauty is operationalized as the symmetry level of a face.

58. Creating Conceptual Order
Conceptualization
Nominal Definition
Operational Definition
Real World Measurement

59. Operationalization Choices
Conceptualization is the refinement and specification of abstract concepts.
Operationalization is the development of specific research procedures that will result in empirical observations representing those concepts in the real world.

60. Defining Variables and Attributes
An attribute is a characteristic or quality of something (ex: female, old, student).
A variable is a logical set of attributes (ex: gender, age).
Every variable must have two important qualities.
The attributes composing it should be exhaustive.
Attributes must be mutually exclusive.
e.g. Gender

61. Operationalization Choices
Range of Variation
To what extent is the research willing to combine attributes in fairly gross categories?
Variation between the Extremes
To what degree is the operationalization of variables precise?
Dimensions

62. Levels of Measurement
Nominal
Ordinal
Interval
Ratio

63. Levels of Measurement – Nominal
Variables whose attributes have only the characteristics of exhaustiveness and mutually exclusiveness.
Categorical
Examples: gender, college major, hair color, birthplace, nationality

64. Levels of Measurement – Ordinal
Variables with attributes we can logically rank order.
Examples: socioeconomic status, level of conflict, conservativeness
The distance between attributes has NO meaning.

65. Levels of Measurement – Interval
Variables for which the actual distance between attributes has meaning.
Examples: temperature (Fahrenheit, Celsius), IQ score

66. Levels of Measurement – Ratio
Variables whose attributes meet the requirements of a interval measure, and has a true zero point.
Examples: temperature (Kelvin), age, length of time, number of groups, number of As received in college

68. Implications of Levels of Measurement
Analyses require minimum levels of measurement.
Some variables can be treated as multiple levels of measurement.
Single or Multiple Indicators

69. Criteria of Measurement Quality
Precision and Accuracy
Reliability
Validity

70. Precision and Accuracy
Precise measures are superior to imprecise ones.
Precision is not the same as accuracy.

71. Reliability – That quality of measurement method that suggests that the same data would have been collected each time in repeated observations of the same phenomenon.
Reliability is not the same as accuracy.

72. Reliability of Research Workers
Test-Retest Method
To make the same measurement more than once.
Split-Half Method
Multiple sets of randomly assigned variables should produce the same classifications
Established Measures
Reliability of Research Workers

73. Validity – a term describing a measure that accurately reflects the concept it is intended to measure.
Face Validity – That quality of an indicator that makes it seem a reasonable measure of some variable.
Criterion-Related Validity – The degree to which a measure related to some external criterion.
Construct Validity – The degree to which a measure relates to other variables as expected within a system of theoretical relationships.
Content Validity – The degree to which a measure covers the range of meanings included within a concept.