DOCSLIB.ORG

Examining Spillover Priming Effects from a Network Perspective

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Examining Spillover Priming Effects from a Network Perspective COME A LITTLE CLOSER: EXAMINING SPILLOVER PRIMING EFFECTS FROM A NETWORK PERSPECTIVE David Thomas Morin A Dissertation Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY August 2013 Committee: Gi Woong Yun, Ph.D., Advisor Mary M. Murray, Ed.D. Graduate Faculty Representative Sung-Yeon Park, Ph.D. Srinivas Melkote, Ph.D. ii © 2013 David Thomas Morin All Rights Reserved iii ABSTRACT Gi Woong Yun, Advisor Priming theory has been well researched within the field of media studies. Since the late 1980s, priming theory has been used to explain a host of media effects related phenomena. Although priming is one of the most robust theories in media studies, scant research has been paid to spillover/indirect priming effects. Traditional media priming studies examine how primes affect individual evaluations of presidents, but none to date have attempted to examine how individuals perceive little-known political officials via strong or weak ties to a president. To address this glaring gap in the literature, a 3X2 online experiment, manipulating prime valence and tie strength, was conducted. More specifically, a news transcript was manipulated to portray the educational issue, Race to the Top, in either a positive, negative, or neutral tone, with President Obama being portrayed as responsible for the issue. A newspaper article was manipulated to portray a fictional congressional candidate named Steve Easterly as either strongly or weakly tied to President Obama. After exposure to the primes, participants were asked to answer a series of items measuring attitude evaluations and voting intent towards both President Obama and Steve Easterly in a post-test questionnaire. A total of 205 (n = 205) politically engaged individuals were recruited across six Midwestern states. Significant differences were found for tie strength along the majority of evaluative measures. In addition, both tie strength and political ideology were found to be significant factors when predicting evaluations and voting intent towards Steve Easterly. When analyzed along party affiliation/membership, significant differences were found between Democrats and Republicans, with Democrats rating Steve Easterly significantly higher along the dependent evaluative criteria. Results are discussed in terms of network theory and motivated iv reasoning among political partisans. More specifically, the results contribute to network theory as they provide a new definition of hub status. The results support previous political psychology research finding conservatives are more likely to have a higher need for closure than their liberal counterparts. Limitations and future research are addressed as well. v Dedicated to the teachers who never stopped encouraging me to ask questions. vi ACKNOWLEDGMENTS I would like to thank several individuals who have provided assistance before and during the dissertation process. First, I want to extend my deepest thanks to my dissertation committee chair, Dr. Gi Woong Yun. Without his valuable insight, humor, and support, I would not have been able to finish this project. I will always be grateful for what he has done for me academically, professionally, and personally. I would also like to thank the rest of my dissertation committee, including Dr. Sung-Yeon Park, Dr. Srinivas Melkote, and Dr. Mary Murray. Your feedback and aid was vital during this phase of my graduate studies. In addition to thanking my academic mentors, I would also like to extend my most sincere gratitude towards two people in my life who were always there to provide guidance whenever I needed it. To Brooke James and Michelle Glass, I will always be thankful for your willingness to listen and offer sound counsel, even when I went off on my tangents. I will always be grateful and appreciative of what both of you have done. Several members of my family have been central figures during this whole process. To my father, thank you for encouraging me to think for myself and to continue my education. Your passion for politics has left an indelible mark on my scholarship and research interests. To my Aunt Deed and Cousin Katherine, thank you for listening and reminding me to stay humble. I will always appreciate your love and support. To my Grandma and Pop, thank you for continuing to stay interested in my topic and inquiring about my progress. I would like to acknowledge the support and guidance offered by my colleagues and friends in the graduate program. To Mark Flynn and Alex Stana, your advice, understanding, and encouragement have helped me to fine-tune my scholarly ability and improve upon my teaching skills. Both of you are not only my colleagues, but my good friends as well. vii Finally, I would like to extend my thanks to two teachers who helped cultivate my love for learning. To Mr. James McCabe and Mr. C.J. Kersey, your own enthusiasm for teaching and asking the pertinent questions influenced my research interests and ultimately my career path. viii TABLE OF CONTENTS Page CHAPTER I. INTRODUCTION ........................................................................................... 1 Academic and Theoretical Significance ................................................................................ 6 Implications of Synthesizing Two Theories and Further Theoretical Needs ............ 11 Additional Dimension: Network Theory .................................................................. 13 Research Method ....................................................................................................... 19 CHAPTER II. LITERATURE REVIEW .............................................................................. 22 Agenda Setting .......................................................................................................... 22 Priming ........................................................................................................... 34 Network Theory ........................................................................................................ 44 CHAPTER III. RESEARCH QUESTIONS ......................................................................... 61 Research Questions ................................................................................................... 61 Direct Priming Questions .......................................................................................... 66 Spillover/Indirect Priming Questions ........................................................................ 74 Political Party Affiliation/Membership and Priming Questions ............................... 81 CHAPTER IV. METHOD .................................................................................................... 84 Overview and Procedure ........................................................................................... 84 Participants ........................................................................................................... 87 Manipulated Priming Stimuli .................................................................................... 88 Measures ........................................................................................................... 90 CHAPTER V. RESULTS ..................................................................................................... 96 Descriptive Results .................................................................................................... 96 ix Results ........................................................................................................... 106 Political Party Afflation/Membership and Priming Results ...................................... 129 Democrats and Priming Effects ................................................................................ 140 Republicans and Priming Effects .............................................................................. 145 CHAPTER VI. DISCUSSION .............................................................................................. 151 Direct Priming Results .............................................................................................. 151 Spillover/Indirect Priming Results ............................................................................ 156 Political Affiliation/Membership and Priming Effects ............................................. 164 Limitations ........................................................................................................... 170 Future Research ......................................................................................................... 173 REFERENCES ........................................................................................................... 180 APPENDIX A. INFORMED CONSENT COPY ................................................................. 209 APPENDIX B. FIRST INVITATION EMAIL COPY ......................................................... 210 APPENDIX C. SECOND INVITATION EMAIL COPY .................................................... 211 APPENDIX D. NEWS TRANSCRIPT PRIME ................................................................... 212 APPENDIX E. NEWSPAPER PRIME ................................................................................. 218 APPENDIX F. DUMMY NEWS TRANSCRIPT AND NEWSPAPER ARTICLE ............ 220 APPENDIX G. QUESTIONNAIRE ..................................................................................... 223 APPENDIX H. FINAL WEBPAGE COPY ........................................................................
Load more

Recommended publications
  • Artificial Intelligence, Automation, and Work
    Artificial Intelligence, Automation, and Work The Economics of Artifi cial Intelligence National Bureau of Economic Research Conference Report The Economics of Artifi cial Intelligence: An Agenda Edited by Ajay Agrawal, Joshua Gans, and Avi Goldfarb The University of Chicago Press Chicago and London The University of Chicago Press, Chicago 60637 The University of Chicago Press, Ltd., London © 2019 by the National Bureau of Economic Research, Inc. All rights reserved. No part of this book may be used or reproduced in any manner whatsoever without written permission, except in the case of brief quotations in critical articles and reviews. For more information, contact the University of Chicago Press, 1427 E. 60th St., Chicago, IL 60637. Published 2019 Printed in the United States of America 28 27 26 25 24 23 22 21 20 19 1 2 3 4 5 ISBN-13: 978-0-226-61333-8 (cloth) ISBN-13: 978-0-226-61347-5 (e-book) DOI: https:// doi .org / 10 .7208 / chicago / 9780226613475 .001 .0001 Library of Congress Cataloging-in-Publication Data Names: Agrawal, Ajay, editor. | Gans, Joshua, 1968– editor. | Goldfarb, Avi, editor. Title: The economics of artifi cial intelligence : an agenda / Ajay Agrawal, Joshua Gans, and Avi Goldfarb, editors. Other titles: National Bureau of Economic Research conference report. Description: Chicago ; London : The University of Chicago Press, 2019. | Series: National Bureau of Economic Research conference report | Includes bibliographical references and index. Identifi ers: LCCN 2018037552 | ISBN 9780226613338 (cloth : alk. paper) | ISBN 9780226613475 (ebook) Subjects: LCSH: Artifi cial intelligence—Economic aspects. Classifi cation: LCC TA347.A78 E365 2019 | DDC 338.4/ 70063—dc23 LC record available at https:// lccn .loc .gov / 2018037552 ♾ This paper meets the requirements of ANSI/ NISO Z39.48-1992 (Permanence of Paper).
    [Show full text]
  • EPA Administrator Lisa P. Jackson Schedule
    Release 4 - HQ-FOI-01268-12 All emails sent by "Richard Windsor" were sent by EPA Administrator Lisa Jackson 01268-EPA-5928 Noah Dubin/DC/USEPA/US To 01/26/2012 06:15 PM cc bcc Richard Windsor Subject 01/30/2012 thru 02/12/2012 Schedule for Lisa P. Jackson *** Do not copy or forward this information *** EPA Administrator Lisa P. Jackson Schedule 01/26/2012 06:11:57 PM Monday, 1/30/2012 08:45 AM-09:15 AM Daily Briefing Location: Administrator's Office ------------------------------- 09:30 AM-10:30 AM HOLD: WH POST-SOTU Ct: Ryan Robison - 202-564-2856 Location: Administrator's Office ------------------------------- 10:30 AM-11:00 AM Personnel Discussion Ct:Ryan Robison - 202-564-2856 Staff: Diane Thompson, Jose Lozano (OA) Paul Anastas (ORD) Optional: Bob Perciasepe (OA) Location: Administrator's Office ------------------------------- 11:00 AM-09:00 PM Out of Office See EA or Jose Location: NYC ------------------------------- 01:00 PM-02:00 PM FYI: Senior Staff Location: Bullet Room ------------------------------- Tuesday, 1/31/2012 09:30 AM-10:30 AM HOLD: WH POST-SOTU Ct: Ryan Robison - 202-564-2856 Location: Administrator's Office ------------------------------- 10:30 AM-10:45 AM Depart for White House Location: Ariel Rios ------------------------------- 10:45 AM-12:15 PM Cabinet Meeting Ct: Liz Ashwell 564.1008 Full Cabinet Meeting w/ POTUS and VPOTUS Location: Cabinet Room, White House ------------------------------- 12:15 PM-12:30 PM Depart for Ariel Rios Release 4 - HQ-FOI-01268-12 All emails sent by "Richard Windsor" were sent by EPA Administrator Lisa Jackson Location: White House ------------------------------- 12:45 PM-12:50 PM Drop-By Meeting with Alaska Eskimo Whaling Commission Ct: Earl Comstock - 202-255-0273 **AA DePass will be lead on this meeting, the Administrator will drop by if her schedule permits **This meeting will last from 12:45 to 1:15 -Mr.
    [Show full text]
  • The Work Ahead Machines, Skills, and U.S
    Independent Task Force Report No. 76 The Work Ahead Machines, Skills, and U.S. Leadership in the Twenty-First Century John Engler and Penny Pritzker, Chairs Edward Alden, Project Director Laura Taylor-Kale, Deputy Project Director ENDNOTES 1. Bureau of Labor Statistics, “Labor Force Statistics From Current Population Survey: Databases, Tables and Calculators by Subject,” February 16, 2018, http://data.bls.gov /timeseries/LNS11300000. See also Arne L. Kalleberg and Till M. von Wachter, “The U.S. Labor Market During and After the Great Recession: Continuities and Transformations,” RSF: The Russell Sage Foundation Journal of the Social Sciences 3, no. 3 (April 2017): 1–19, http://rsfjournal.org/doi/full/10.7758/RSF.2017.3.3.01; Sandra E. Black, Diane Whitmore Schanzenbach, and Audrey Breitwieser, “The Recent Decline in Women’s Labor Force Participation,” Hamilton Project, October 2017, http:// hamiltonproject.org/assets/files/decline_womens_labor_force_participation_ BlackSchanzenbach.pdf. While labor force participation did fall more steeply during the recession, there has been a reasonably steady decline since 2000 driven by rising retirements and declining work among prime-age men. See Alan B. Krueger, “Where Have All the Workers Gone? An Inquiry Into the Decline in the U.S. Labor Force Participation Rate,” Brookings Papers on Economic Activity, September 2017, http:// brookings.edu/bpea-articles/where-have-all-the-workers-gone-an-inquiry-into-the -decline-of-the-u-s-labor-force-participation-rate. 2. Annie Lowrey, “The Great Recession Is Still With Us,” Atlantic, December 1, 2017, http://theatlantic.com/business/archive/2017/12/great-recession-still-with-us/547268. 3.
    [Show full text]
  • Structural Balance and Partitioning Signed Graphs
    Structural Balance and Partitioning Signed Graphs Patrick Doreian Andrej Mrvar Department of Sociology Faculty of Social Sciences University of Pittsburgh University of Ljubljana Abstract Signed graphs have been used frequently to model affect ties for social actors. In this context, structural balance theory has been used as a theory for the organization and form of these relations. Based on a graph theoretical formalization of this theory, for signed graphs, there are theorems stating that balanced structures have clear parti- tioned forms. We discuss the use of local optimization procedures as a method of obtaining these partitioned structures – or partitioned structures that are as close to a balanced partition as possible for structures that are not balanced. In addition, this method provides a measure of the extent to which a signed graph is imbalanced. For a time series of signed graphs, this permits a test of the balance hypoth- esis that human groups tend towards balance over time. Examples are provided of interpersonal ties in networks and institutionalized rela- tions among collective units. Since the pioneering work of Heider (1946) there has been an enduring concern with theories of structural balance. See, for example, Taylor (1970) and Forsythe (1990). Central to this formulation is the idea of triads made up of two actors, p and q, and some object, x. There is a direct social relation between the two actors and there are unit formation links between the actors and the object. The set of such triads is displayed in Figure 1. The relation between the actors can be positive (for example, liking) or negative (disliking) and the unit formation relations can be positive (for example, approve) or negative (disapprove).
    [Show full text]
  • Administration of Barack Obama, 2014 Remarks on the Nomination Of
    Administration of Barack Obama, 2014 Remarks on the Nomination of Maria Contreras-Sweet To Be Administrator of the Small Business Administration January 15, 2014 Please have a seat. Thank you so much. Well, welcome to the White House. And I am pleased to be joined by many of the people on the frontlines when it comes to creating jobs and new opportunities: America's small-business owners. And I want to thank all of them for the hard work and the sacrifice of these entrepreneurs, as well as the workers and the families across the country that have helped us pull ourselves out of one of the worst recessions in our history. Now what we're seeing is businesses having created more than 8 million new jobs since we hit bottom. Manufacturing is growing, led by a booming auto industry. Our investments have helped bring about new technologies, more affordable energy, and are slowing health care costs, all of which are making America even more attractive for investors. And we're starting to see a lot of the jobs that had left our shores in manufacturing, for example, starting to come back, because we put ourselves in a much more competitive position. And so all the pieces are there to bring back even more new jobs to America this year, but it's not going to happen by itself. This has to be a year of action. We've got to keep our economy growing. We've got to make sure that our working families are sharing in growth and increasing success.
    [Show full text]
  • Balance and Fragmentation in Societies with Homophily and Social Balance Tuan M
    www.nature.com/scientificreports OPEN Balance and fragmentation in societies with homophily and social balance Tuan M. Pham1,2, Andrew C. Alexander3, Jan Korbel1,2, Rudolf Hanel1,2 & Stefan Thurner1,2,4* Recent attempts to understand the origin of social fragmentation on the basis of spin models include terms accounting for two social phenomena: homophily—the tendency for people with similar opinions to establish positive relations—and social balance—the tendency for people to establish balanced triadic relations. Spins represent attribute vectors that encode G diferent opinions of individuals whose social interactions can be positive or negative. Here we present a co-evolutionary Hamiltonian model of societies where people minimise their individual social stresses. We show that societies always reach stationary, balanced, and fragmented states, if—in addition to homophily— individuals take into account a signifcant fraction, q, of their triadic relations. Above a critical value, qc , balanced and fragmented states exist for any number of opinions. Te concept of so-called flter bubbles captures the fragmentation of society into isolated groups of people who trust each other, but clearly distinguish themselves from “other”. Opinions tend to align within groups and diverge between them. Interest in this process of social disintegration, started by Durkheim 1, has experienced a recent boost, fuelled by the availability of modern communication technologies. Te extent to which societies fragment depends largely on the interplay of two basic mechanisms that drive social interactions: homophily and structural balance. Homophily is the “principle” that “similarity breeds connection”2. In particular, for those individuals who can be characterised by some social traits, such as opinions on a range of issues, homophily appears as the tendency of like-minded individuals to become friends 3.
    [Show full text]
  • Annual Report M Ission
    2012 ANNUAL REPORT M ISSION The New England Council is an alliance of businesses, academic and health institutions, and public and private organizations throughout New England formed to promote economic growth and a high quality of life in the New England region. The New England Council is a leading voice on the issues that shape the region’s economy and quality of life. The Council focuses on key industries that drive the region’s economic growth including education, energy, transportation, technology and innovation, healthcare and financial services. THE NEW ENGLAND COUNCIL TABLE OF CONTENTS 2012 4 President’s Letter 5 Chairman’s Letter ADVOCACY & INITIATIVES 6 Overview 6 Defense 8 Energy & Environment 10 Financial Services 12 Healthcare 13 Higher Education 15 New England Economic Partnership 16 Smart Infrastructure Report 17 Technology 19 Transportation EVENTS 20 Annual Dinner 22 Annual Spring Event 24 Congressional Roundtable Series 26 Featured Events 27 Governors’ Forums 28 Politics & Eggs Series ABOUT THE COUNCIL 29 DC Dialogue 30 Board of Directors 34 New Members 3 THE NEW ENGLAND COUNCIL 2012 PRESIDENT’S LETTER DEAR NEW ENGLAND COUNCIL MEMBER: As I look back at 2012, I am once again truly astounded at how much The New England Council has accomplished during the past year. Over the course of my 16 years at the helm of The New England Council, it has been remarkable to watch the organization evolve and grow as each year passes. When people ask me how we continue to thrive—particularly during the challenging economic situation in recent years—I tell them that it is because of our members.
    [Show full text]
  • Chapter 5 Positive and Negative Relationships
    From the book Networks, Crowds, and Markets: Reasoning about a Highly Connected World. By David Easley and Jon Kleinberg. Cambridge University Press, 2010. Complete preprint on-line at http://www.cs.cornell.edu/home/kleinber/networks-book/ Chapter 5 Positive and Negative Relationships In our discussion of networks thus far, we have generally viewed the relationships con- tained in these networks as having positive connotations — links have typically indicated such things as friendship, collaboration, sharing of information, or membership in a group. The terminology of on-line social networks reflects a largely similar view, through its em- phasis on the connections one forms with friends, fans, followers, and so forth. But in most network settings, there are also negative effects at work. Some relations are friendly, but others are antagonistic or hostile; interactions between people or groups are regularly beset by controversy, disagreement, and sometimes outright conflict. How should we reason about the mix of positive and negative relationships that take place within a network? Here we describe a rich part of social network theory that involves taking a network and annotating its links (i.e., its edges) with positive and negative signs. Positive links represent friendship while negative links represent antagonism, and an important problem in the study of social networks is to understand the tension between these two forces. The notion of structural balance that we discuss in this chapter is one of the basic frameworks for doing this. In addition to introducing some of the basics of structural balance, our discussion here serves a second, methodological purpose: it illustrates a nice connection between local and global network properties.
    [Show full text]
  • Chapter 5 Positive and Negative Relationships
    Chapter 5 Positive and Negative Relationships Often, knowing just the nodes and edges of a network is not enough to understand the full picture — in many settings, we need to annotate these nodes and edges with additional information to capture what’s going on. This is a theme that has come up several times in our discussions already: for example, Granovetter’s work on the strength of weak ties is based on designating links in a social network as strong or weak, and empirical analyses of social networks that evolve over time is based on annotating edges with the periods during which they were “alive.” Here we describe a rich part of social network theory that involves annotating edges with positive and negative signs — to convey the idea that certain edges represent friendship, while other edges represent antagonism. Indeed, an important problem in social networks is to understand the tension between these two forces, and the notion of structural balance that we discuss is one of the basic frameworks for doing this. In addition to introducing some of the basics of structural balance, our discussion here serves a second, methodological purpose: it illustrates a nice connection between local and global network properties. A recurring issue in the analysis of networked systems is the way in which local effects — phenomena involving only a few nodes at a time — can have global consequences that are observable at the level of the network as a whole. Structural balance offers a way to capture one such relationship in a very clean way, and by purely mathematical analysis: we will consider a simple definition abstractly, and find that it inevitably leads to certain macroscopic properties of the network.
    [Show full text]
  • Structural Balance in Signed Networks: Separating the Probability to Interact from the Tendency to Fight∗
    Structural Balance in Signed Networks: Separating the Probability to Interact from the Tendency to Fight∗ J¨urgenLernery Abstract Structural balance theory implies hypothetical network effects such as \the enemy of an enemy is a friend" or \the friend of an enemy is an enemy." To statistically test such hypotheses researchers often estimate whether, for instance, actors have an increased probability to collaborate with the enemies of their enemies and/or a decreased probability to fight the enemies of their enemies. Empirically it turns out that the support for balance theory from these tests is mixed at best. We argue that such results are not necessarily a contradiction to balance theory but that they could also be explained by other network effects that influence the probability to interact at all. We propose new and better interpretable models to assess structural balance in signed networks and illustrate their usefulness with networks of international alliances and conflicts. With the new operationalization the support for balance theory in international relations networks is much stronger than suggested by previous work. Keywords: signed networks, structural balance theory, international re- lations, conditional sign of interaction 1 Introduction Generalizing Heider's theory of cognitive balance (Heider 1946), Cartwright and Harary (1956) called a signed network structurally balanced if every cycle has an even number of negative ties. They proved that a network is balanced if and only if its actors can be divided into two groups with only positive ties within the groups and only negative ties between groups. The fundamental claim of structural balance theory is that actors have a preference for balanced states and if a network is unbalanced then actors have a tendency to increase balance by adapting their ties.
    [Show full text]
  • Structural Balance in Signed Digraphs: Considering Transitivity to Measure Balance in Graphs Constructed by Using Different Link Signing Methods
    Structural balance in signed digraphs: considering transitivity to measure balance in graphs constructed by using different link signing methods Ly Dinh*, Rezvaneh Rezapour*, Lan Jiang, Jana Diesner University of Illinois at Urbana{Champaign * These authors contributed equally to this work Abstract Structural balance theory assumes triads in networks to gravitate towards stable configurations. The theory has been verified for undirected graphs. Since real-world networks are often directed, we introduce a novel method for considering both transitivity and sign consistency for calculating balance in signed digraphs. We test our approach on graphs that we constructed by using different methods for identifying edge signs: natural language process- ing to infer signs from underlying text data, and self-reported survey data. Our results show that for various social contexts and edge sign detection methods, balance is moderately high, ranging from 67.5% to 92.4%. Keywords: Structural balance, Transitivity, Signed digraphs, Natural language processing, Communication networks, Organizational networks 1. Introduction Real-world social and communication networks are composed of complex arXiv:2006.02565v1 [cs.SI] 3 Jun 2020 and continually evolving interactions among social agents. Network scholars have examined core principles that explains patterns of social interactions at various levels of analysis, i.e., at the node level [4], dyadic level [3], triadic level [5, 30], subgroup level [44], and the graph level [31]. Each level of analysis enables different types of hypotheses to be tested, e.g., with respect Email address: {dinh4,rezapou2,lanj3,jdiesner}@illinois.edu (Ly Dinh*, Rezvaneh Rezapour*, Lan Jiang, Jana Diesner) to structural properties, such as reciprocity at the dyad level, transitivity at the triad level, clusterability at the subgroup level, and centralization at the network level [54, 35].
    [Show full text]
  • A Simple Approach for Quantifying Node Centrality in Signed and Directed Social Networks Wei-Chung Liu1 , Liang-Cheng Huang1, Chester Wai-Jen Liu2 and Ferenc Jordán3*
    Liu et al. Applied Network Science (2020) 5:46 Applied Network Science https://doi.org/10.1007/s41109-020-00288-w RESEARCH Open Access A simple approach for quantifying node centrality in signed and directed social networks Wei-Chung Liu1 , Liang-Cheng Huang1, Chester Wai-Jen Liu2 and Ferenc Jordán3* * Correspondence: jordan.ferenc@ gmail.com Abstract 3Balaton Limnological Institute, MTA Centre for Ecological Research, The position of a node in a social network, or node centrality, can be quantified in Klebelsberg Kuno, Tihany 3, 8237, several ways. Traditionally, it can be defined by considering the local connectivity of Hungary a node (degree) and some non-local characteristics (distance). Here, we present an Full list of author information is available at the end of the article approach that can quantify the interaction structure of signed digraphs and we define a node centrality measure for these networks. The basic principle behind our approach is to determine the sign and strength of direct and indirect effects of one node on another along pathways. Such an approach allows us to elucidate how a node is structurally connected to other nodes in the social network, and partition its interaction structure into positive and negative components. Centrality here is quantified in two ways providing complementary information: total effect is the overall effect a node has on all nodes in the same social network; while net effect describes, whether predominately positive or negative, the manner in which a node can exert on the social network. We use Sampson’s like-dislike relation network to demonstrate our approach and compare our result to those derived from existing centrality indices.
    [Show full text]