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Network Analysis Lim 97
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  • Although there are lots of attitude definitions, this study follows Fazio’s definition. That is, attitudes can be defined as associations, represented in memory, between attitude objects and their evaluations. In this definition, there are two key properties, attitude object and evaluation. Attitude objects are anything that can be designated including concrete objects and abstract objects. Concrete objects are such as desk, chair, car, dog, cat, and human beings, and abstract objects are such as freedom, power, good, bad, and poor. So, attitude objects can be considered symbols or concepts that can be expressed by a language. Second key property of attitude is evaluation. Evaluation is a summary assessment including all aspects of evaluative responding, such as cognitive beliefs, emotions, and past behaviors. That is, when we evaluate an attitude object, we consider our beliefs based on our knowledge. Also, we consider our emotions, such as happy, sad, guilty, and angry. Finally, we consider our past experience. So, an attitude can be represented as a simple two-node network like this diagram.
  • An attitude is often associated with other attitudes. The associations among attitudes are called interattitude structure. Traditionally, interattitude structure have been studied. Balance theory is the most representative. The diagram is a simple example based on the balance theory. Now, I will explain the diagram using my wife case. My wife is allergic to chicken, so she has a negative evaluation of all chicken cuisine. When I asked her “how about duck couisine?”, she said “I don’t like duck either because it is a kind of chicken.” In my wife’s case, the attitude toward duck is associated with the attitude toward chicken. From this simple example, we can consider that attitudes are interrelated to each other rather than isolated in our minds.
  • Although I simply explained the interattitude structure, it’s not simple. We know that a neuron in our brain stores information and it is interconnected to other neurons. Also, the neural networks in our brain are very complex like the left figure. This may indicate that the interattitude structure in our brains is very complicated. The Galileo model considers the complex neural networks in our brains and attempt to mimic and describe the interattitude structure in a multi-dimensional space as the right figure.
  • First, the Galileo model considers the categorization process that is a basic cognitive process in human brains. Through the categorization process, we can easily recognize our world. For your better understanding, I’d like to give a simple example based on my son’s case. I have a son. He is three years old. He likes apple juice but he doesn’t like milk. One day, I gave him a lemonade instead of apple juice. Actually, he had never seen the lemonade. He sipped a lemonade then he looked like thinking for a while. Then, he said to me “lemonade is apple juice. I like it.” So, I asked him, “how about milk?” He said, “Milk is different. It is not apple juice.” In my son’s case, he categorized his favorite by using apple juice. That is, lemonade is included in apple juice category but milk is not. The categorization process is based on similarity and dissimilarity between objects. Likewise, although my son is only three years old. He is able to perceive the world by using the categorization process. So, the categorization process is basic and inevitable to understand our world.
  • Second, the Galileo space is a cognitive map in human brains. As I said before, the Galileo model mimics the neural networks in our brains. That is, the Galileo model is mapping the mental structure. The Galileo model measures the concept distances based on the dissimilarity between every possible pair of concepts. In my son’s case, lemonade and apple juice are very similar concepts. So, their positions in the Galileo space are very close to each other. On the contrary, milk is different from lemonade and apple juice. So. The position of milk is relatively far from the other concepts. That is, the Galileo model makes a simple cognitive map considering concept distances.
  • Lastly, the self concept is a very special concept in the Galileo model. It is a conscious representation of a person. In the neuroscience, many researchers empirically found differentiated neural activations in self-related cognitive process. These findings supports that the representation of self exists as distinct information processing in human brains. In the Galileo space, like the other concepts, the self concept is close to relevant concepts that describe the person. Conversely, it is far from irrelevant concepts that do not define the person. In my son’s case, apple juice and lemonade may be close to his self concept, but milk may be far from the self in the Galileo space. So, an attitude can be identified as the distance between the self concept and the designated concept. Lastly, the Galileo measure is the direct-magnitude scaling for precise measurement. The scaling is based on the real number system including absolute zero point and unbounded real number. So, the scaling can be fully satisfied with the property of ratio scale and mathematical operations.
  • To examine the interattitude structure of the target audiences in IDCs, the Galileo survey was conducted. This study used a convenient sample of college students as a segment of the campaign targets. The Galileo survey instrument is constructed by the 12 concepts. So, a complete list of 66 pair comparisons was included in the survey instrument.
  • This is an example of the Galileo survey. Cooperation and conflict are 100 units apart. That is the criterion pair which helps the respondents to judge the differences between concepts as a standard distance. Respondents were instructed to report a real number without any upper limit. But note that , a number less than 100, it means that the differences between any paired concepts are less different than the standard distance. A number above 100, it means that the differences are more different. Also, if any paired concept is perceived to be the same, zero point should be entered. Lastly, if respondents do not know the differences, blank answers were allowed.
  • To better understand the distances among concepts, this figure represents the interrelationships among 12 concepts in the three dimensional space accounting for about 67% of the real variance. As you can see, poverty and international aid are very far from the self concept. Also, international aid does not have neighboring concepts. On the contrary, health, education and human rights are relatively close to the self concept.
  • This diagram shows the Galileo message strategy based on the target audiences’ interattitude structure. As you can see, if a campaign message emphasizes the strong connections between international aid and the three relevant concepts, such as education, health, and human rights, the combined pulling effects of the three concepts will move the international aid close to the self concept. The principle of the Galileo message strategy is simple. Actually, it’s basic physics. I will show you a practical example. Could you help me? The Galileo message strategy is based on the mathematical representation of physical vector in the spatial coordinate system. So, the Galileo message optimizing procedure is calculating all possible concept combinations from one to four concept combinations. Then, through the message optimizing procedure, the Galileo results shows the best concept pair that makes the best expected position of international aid close to the target. As you can see, if the full effects of the best message strategy were obtained, the distance between the self concept and the expected position of international aid becomes 14.41 units. It’s very close.
  • Based on the Galileo message strategy, I made a simple campaign message like this. As you can see, the message does not include emotional and negative concepts.
  • The different concept locations is graphically displayed as the figure. As you can see, non-manipulated concept locations are relatively stable across the three group spaces, whereas the manipulated concept locations are relatively different. Particularly, the locations of international aid are more different than others.
  • This table presents the differences of manipulated concept-pair distances. As you can see, all distances in two treatment groups decreased. Particularly, the distances between international aid and the self concept relatively more decreased. The results of Kruska-Wallis and Mann Whitney U test indicated that the distances are significantly different and the distances in the two treatment groups are smaller than the distances in the control group. These results statistically supports the Galileo message effectiveness for attitude change.

Transcript

  • 1. Yon Soo Lim, Ph.D. Research Fellow WCU Webometrics Institue Yeungnam University [email_address]
  • 2. Network Analysis
    • Network analysis is a set of research procedures used for identifying structures in social systems based on the relations among a system’s components (Richards & Barnett, 1993; Rogers & Kincaid, 1981).
  • 3. Network Analysis
  • 4. Network Analysis
    • Node
      • Unit of analysis (individual or higher-level component)
      • Other terms: actors, points or vertices
    • Link
      • Relationship between nodes
      • Other terms: lines, edges or geodesics
  • 5. Network Analysis
    • Social/communication network analysis
    • Semantic network analysis
    • Neural network analysis
  • 6. Social Network Analysis
      • Social network analysis is a set of research procedure identifying the structure of communication relationships and flows among components in a social system, such as people, groups, organizations, nations, and other information processing entities.
    • Software
      • UCINET (Borgatti, Everett & Freeman)
      • MULTINET (Richards & Seary)
      • NETMINER (Cyram)
      • PAJEK (Batagelij & Mrvar)
  • 7. Network Survey Questionnaire Which of these people do you communicate with on a weekly basis? If you communicate with them, please place a one (1) by their name and if you do not communicate with them weekly, place a zero (0) by their name for both business and social non-work issues. If you do speak with them, please indicate whether face-to-face, phone, email, etc. Do you communicate with this person: Business communication Social Non-work Resources Used Ed Peet       Karen Shed       Carlton Smith       Tracy Pope       Dr. Todd McCune       Dr. Linda Clark       Jennifer Heisner       Melanie Lowe       Cindy VanMeter       Tracy Gilmore       Beth Murnane       Bill Morrison       Tom Redmond       Rene Kunego       Joanne McIllwaine       Frank Blasioli       Sue Ann Burley       Vivian Bulriss      
  • 8. Results of Social Network Analysis Business Communication Social Communication
  • 9. A Cross-Cultural Comparison of Online Forum Structures on MMOGs Power: Red > Yellow > Green Korea United States
    • Number of Nodes = 4,384
    • Number of Links = 9,304
    • Density = 0.000951
    • Centralization = 24.8%
    • Number of Nodes = 10,966
    • Number of Links = 28,268
    • Density = 0.000458
    • Centralization = 11.4%
  • 10. International Aid Network
  • 11. Int’ Telecommunication Network
  • 12. Semantic Network Analysis
    • Semantic network analysis is a systematic technique of content analysis to identify the meaning structure of symbols or concepts in a set of documents by using network analysis (Monge & Contractor, 2003; Monge & Eisenberg, 1987).
    • Semantic network represents a relationship of shared understanding of cultural products among members in a social system (Monge & Contractor, 2003).
  • 13. CATPAC
    • A popular software for semantic network analysis
    • A self-organizing artificial neural network
      • Keyword identification
      • Cluster analysis (dendogram)
      • MDS
    • Explore the pattern of interrelationship among words based on the probability of their co-occurrence
  • 14. Semantic networks (Blogs vs. Newspapers) Centralization = 19.6% Blogs Newspapers Centralization = 44.2%
  • 15. Semantic networks (Progressive vs. Conservative) Centralization = 20.0% Progressive News Conservative News Centralization = 46.6%
  • 16. Semantic Network of IDCs
  • 17. Neural Network Analysis
      • Neural network analysis is modeling dynamic attitudinal structures and cognitive processes based on natural neural networks in human brains.
  • 18. Defining Attitude
    • Attitudes can be defined as associations, represented in memory, between attitude objects and their evaluations (Fazio, 1990; 1995).
      • Attitude objects: anything that can be designated
      • Evaluations: summary assessments considering cognitive, affective, and behavioral associations
    Attitude Object Evaluation Attitude
  • 19. Interattitude Structure
    • A simple example
    Evaluation “ I don’t like chicken because I am allergic to chicken.” “ I don’t like duck either because it is a kind of chicken.” Chicken Duck
  • 20. Galileo Spatial-linkage Model
    • Neural networks in human brains
    • The model represents interattitude structure within a spatial coordinate system.
    • Theoretical properties
      • Categorization
      • Cognitive map
      • Self-concept
  • 21. Categorization
    • Categorization is a basic cognitive process to understand our world.
    • Similarity / Dissimilarity
    ≠ =
  • 22. Cognitive Map
    • Mapping spatial mental structure of human brain
    Mental Structure Galileo Space
  • 23. Self-Concept
    • Conscious representation of a person
    • An attitude can be defined as the distance between the self-concept and the designated concept.
    Galileo Space Myself
  • 24. Example
    • Galileo survey
      • Participants: 218 UB undergraduate students
      • A paper-based survey
      • 12 concepts for the study
      • A complete list of 66 pair comparisons
    Poverty Education Health Human Rights Human Resources Natural Resources Social Safety Governmental Leadership Global Cooperation Global Conflict International Aid Self
  • 25. Example of Galileo Survey
    • If COOPERATION and CONFLICT are 100 units apart, how different or how far apart is each word or phrase from the other in the pair?
    • POVERTY and EDUCATION are __ units apart.
  • 26. Mean Distance Matrix
  • 27. Neural Network
    • Galileo space
  • 28. Message Strategy for IDCs 14.41 units 72.67 units Health International aid Human Rights Education Target (Self) Resultant
  • 29. Message
      • INTERNATIONAL AID is closely related to EDUCATION , HEALTH , and HUMAN RIGHTS .
      • International aid promotes human rights for everyone throughout the world by providing health care and education. We want you to pledge your support. Join the growing global movement for international aid. Your support will help to achieve an increase in international aid, promoting human rights to provide health care and education for everyone in the world.
  • 30.
    • Comparison of the Galileo spaces
  • 31. Comparison of Concept Distances Edu & Health 62.16 (7.02) 59.07 (6.92) 3.09 45.33 (4.63) 16.83 Edu & HR 53.34 (6.66) 47.95 (6.29) 5.39 46.00 (6.37) 7.34 Edu & Aid 68.52 (7.04) 55.76 (7.41) 12.75 47.88 (4.57) 20.64 Health & HR 65.02 (7.33) 50.32 (6.53) 14.69 45.64 (4.79) 19.38 Health & Aid 64.67 (6.80) 55.64 (6.12) 9.03 50.93 (5.33) 13.75 HR & Aid 60.28 (5.94) 49.36 (6.41) 10.92 55.65 (5.50) 4.63 Aid & Self 104.94 (9.44) 76.93 (7.18) 28.01 80.70 (7.03) 24.24 Δ Distance Δ Distance Distance Control (n=65) One-time (n=59) Two-time (n=94) Note. () standard error Kruskal-Wallis Test: χ 2 = 7.043, df = 2, p < .05 Mann-Whitney U test: Control > One-time = Two-time ( p < .05)
  • 32. Discussion
    • Network analysis has been applied for diverse social scientific research.
    • Its practical application has a large scope from individual to international level.
    • However, network analysis has several limitations.
      • Modeling dynamic processes over time
      • Sampling & gathering data
      • Measures (e.g. centrality and density)
  • 33. Resources
    • International Network for Social Network Analysis (INSNA)
    • http://www.insna.org
    • SOCNET - a LISTSERV list, allows network researchers worldwide to discuss research and professional issues, make announcements, and request help from each other.
    • http://www.insna.org/INSNA/socnet.html