Tune in, Log on: Soaps, Fandom, and Online Community
Publication Year: 2000
Subject: New Media & Communication Technology
Tune In, Log Out is an ethnographic study of an Internet soap opera fan group. Bridging the fields of computer-mediated communication and audience studies, the book shows how verbal and non verbal communicative practices create collaborative interpretations and criticism, group humor, interpersonal relationships, group norms and individual identity. While much has been written about problems and inequities women have encountered online, Nancy K Baym's analysis of a female-dominated group in which female communication styles prevail demonstrates that women can build successful online communities while still welcoming male participation. In addition, a longitudinal look at the development of fan group allows an examination of the endurance of the group’s social structure in the face of the Internet’s tremendous growth. Lively and engaging, Tune In, Log Out ...
- Front Matter
- Back Matter
- Subject Index
- Introduction: Three Tales of One Community
- The Structure of Usenet and rec.arts.tv.soaps
- Audience as Community?
- Community as Practice
- Researching rec.arts.tv.soaps
- Stay Tuned for the Rest of This Book
- Chapter 1: The Soap Opera and its Audience: TV for the Less Intelligent?
- The r.a.t.s. Newsgroup as an Alternative
- Then Who is the Soap Opera Audience?
- Understanding the Soap Opera Genre
- Dismissing the Soaps, Take 2: Misreading the Genre or its Viewers
- Chapter 2: Interpreting and Comparing Perspectives in the Audience Community
- Interpretive Practices
- Informative Practices
- The Interpretive Functions of Informative Practices
- Social Functions of Pooling Perspectives
- Chapter 3: It's Only a Soap: Criticism, Creativity, and Solidarity
- Evaluating the Soaps
- Watching despite the Faults
- From Criticism to Humorous Performance
- Criticism and the Creation of Group Identity
- Chapter 4: “I Think of Them as Friends”: Interpersonal Relationships in the Online Community
- Accomplishing Friendliness
- Managing Disagreement
- Ritualized Space for Friendliness
- Dyadic Friendships
- The Limits of Online Friendship
- Influences on the Development of Online Social Norms
- Appropriation and the Creation of Community
- Chapter 5: The Development of Individual Identity
- To Post or to Lurk
- The Computer Medium as an Influence on Identity
- Offline Identities
- Situating Online Identity in an Online Community
- Community Affirmation of Identity
- Chapter 6: Futureflash: 5 Years Later
- Consistency over Time
- New Tensions
- Coping with Change
- From Village to City
- Conclusion: Tune in Tomorrow
- Studying Online Community
- Rethinking Audience Community
- Studying Communities Through Practice
- Toward a Convergent Future
New Media Cultures[Page ii]
Series Editor: Steve Jones
New Media Cultures critically examines emerging social formations arising from and surrounding new technologies of communication. It focuses on the processes, products, and narratives that intersect with these technologies. An emphasis of the series is on the Internet and computer-mediated communication, particularly as those technologies are implicated in the relationships among individuals, social groups, modern and postmodern ways of knowing, and public and private life. Books in the series demonstrate interdisciplinary theoretical and methodological analyses, and highlight the relevance of intertwining history, theory, lived experience, and critical study to provide an understanding of new media and contemporary culture.
Books in this series …
Exploring Technology and Social Space J. Macgregor Wise
CyberSociety 2.0: Revisiting Computer-Mediated Communication and Community edited by Steven G. Jones
Tune In, Log On: Soaps, Fandom, and Online Community Nancy K. Baym
Copyright © 2000 by Sage Publications, Inc.
All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher.
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Printed in the United States of America
Library of Congress Cataloging-in-Publication Data
Baym, Nancy K.
Tune in, log on: Soaps, fandom, and online community/by Nancy K. Baym.
p. cm.—(New media cultures)
Includes bibliographical references (p.) and index.
ISBN 0-7619-1648-2 (cloth)
ISBN 0-7619-1649-0 (paperback)
1. Soap operas—Social aspects—United States. 2. Soap operas—Electronic discussion groups. I. Title. II. Series.
PN1992.8.S4 B39 1999
This book is printed on acid-free paper.
00 01 02 03 04 05 06 7 6 5 4 3 2 1
Acquiring Editor: Margaret H. Seawell
Editorial Assistant: Renée Piernot
Production Editor: Sanford Robinson
Production Assistant: Karen Wiley
Typesetter: Lynn Miyata
Indexer: Mary Mortensen
Cover Design: Candice Harman
This book is the end result of nearly a decade of work that many people have influenced and inspired along the way. Rex Clark introduced me to the social worlds of the Internet in 1990. When I wrote my first paper on this subject in 1991, Nina Baym and Peggy Miller saw immediately that this was “my project.” Many people on the rec.arts.tv.soaps (r.a.t.s.) newsgroup who read that paper encouraged me to pursue the work. Despite my doubts, I figured that when your mom, your dissertation director, and your respondents all want you to keep at it, they probably are right. They were, and I am grateful for their guidance. Many people gave helpful comments including Peggy Miller, Barbara O'Keefe, Ellen Wartella, Cheris Kramarae, Henry Jenkins, Larry Grossberg, Mary Ellen Brown, Robert Sanders, Brenda Danet, and several anonymous reviewers. Julie Snow, Susan Barnett-Lawrence, Rex Clark, Yves Clemmen, Carine Melkom-Mardorossian, and Christine Levecq all have made face-to-face soap viewing much more fun over the years. Stan Kerr of the University of Illinois and Lyle Kipp helped with computing accounts and programming. Mark Huglen helped to code data. In addition to opening my eyes to the Net and watching my soaps, Rex Clark wrote the database I used to handle all these data and had countless conversations about the research with me. Our beautiful son, Zane, kept my priorities obvious. My editor and [Page x]friend, Steve Jones, deserves extra special thanks for patiently remaining convinced that there was a good book here, for working to amplify my voice rather than inserting his own, and for being the only editor out there who is as big a Nick Rudd fan as I am. I never would have written this book without his unwavering encouragement. Thanks also go to Margaret Seawell and Renée Piernot at Sage Publications. The quotations from Liccardo's (1996) and Susman's (1997) articles in Chapter 1 are excerpted from Soap Opera Weekly. Thanks go to Mimi Torchin, editor-in-chief of that fine magazine, for this and her general encouragement (despite her qualms about the Net). Ann Limongello at ABC found photographs of the characters for me to use. Many thanks also go to the colleagues and students at the University of Illinois and Wayne State University who have helped to make my career a pleasure.
Some of the ideas and paragraphs in this book have appeared previously in earlier articles published in the Journal of Folklore Research (1993), the Journal of Computer-Mediated Communication (1995), and Research on Language and Social Interaction (1996) as well as the following books: The Cultures of Computing (1995) edited by Leigh Star, Cyber-Society (1995) and CyberSociety 2.0 (1998) edited by Steve Jones, and Theorizing Fandom: Fans, Subcultures, and Identity (1998) edited by Cheryl Harris and Alison Alexander.
Dozens of people from r.a.t.s. and rec.arts.tv.soaps.abc have generously participated in this study and provided ongoing excitement and encouragement. This book is for them. I hope I have done them justice.
Appendix A: Surveys[Page 219]Survey 1 (Posted to the Newsgroup in the Winter of 1991)
- How do we “define” rec.arts.tv.soaps (r.a.t.s.)?
- How does r.a.t.s. compare to other newsgroups on Usenet or to soap groups on Prodigy, GEnie, or any others?
- What are the r.a.t.s. standards of netiquette? How did you learn them?
- How do we think of the people who post to r.a.t.s.? (obviously, not as housewives with their hair in curlers eating bon-bons!)
- What do you consider your relationship(s) (if any) with people on the Net to be? Do you e-mail with other r.a.t.s. people?
- What makes a r.a.t.s. posting or poster successful? Which ones do you like best and why?
- How do the rest of you read r.a.t.s.? Where? How often?
- Does your involvement with this group influence the way in which you watch the show? Which things you notice? Which characters you like? Other influences (like some people have said, the Net keeps them watching even when the soap gets dull)?
- Does the form or content of the show influence the way in which you read r.a.t.s.? For example, how (if ever) does the show make you want to read or post? Or, make you not want to read r.a.t.s. or post?
[Page 220]I am also curious as to the age range on r.a.t.s., the jobs we hold, and how long you have watched your soaps and read r.a.t.s. If there are other important things I have neglected, please share your thoughts.Survey 2 (Posted to the Newsgroup in the Fall of 1993)
Survey 3 (Posted to the Newsgroup in the Spring of 1998)
- How do you describe rec.arts.tv.soaps (r.a.t.s.) to people who do not know what it is?
- Why do you read and/or post to r.a.t.s.?
- If you are a lurker, what are the reasons why you do not post?
Survey 3 (Version e-mailed Directly to Current and Former Participants in the Spring of 1998)
- When did you first begin reading rec.arts.tv.soaps (r.a.t.s.) or rec.arts.tv.soaps.abc (r.a.t.s.a.)?
- What do you like most about r.a.t.s.a.?
- What do you like least about r.a.t.s.a.?
- In the time that you have been reading r.a.t.s. and/or r.a.t.s.a., what do you think are the most noticeable or important changes that have happened in the newsgroup?
- What do you think are some of the reasons why r.a.t.s.a. has changed as it has?
- In the time that you have been reading r.a.t.s. and/or r.a.t.s.a., what has remained the same?
- What do you think are some of the reasons why these aspects of the group have remained more stable over time?
- How has this group been changed by the World Wide Web?
- Do you maintain or visit Web sites related to this newsgroup? If so, please describe how your soap newsgroup and soap Web use are related.
- What types of relationships do you feel you have with other people who participate in this group?
- How well do you think the term “community” fits this group now? Please explain why.
- How do you think you would have answered Question 11 when you first got to know this group?
- How (if at all) do you think participation in this newsgroup affects your offline life?
- Do you have any other thoughts on this newsgroup, now or over time, that you would like me to consider?
- What is your age?[Page 221]
- What is your gender?
- What is your occupation?
- When did you first begin reading rec.arts.tv.soaps (r.a.t.s.) or rec.arts.tv.soaps.abc (r.a.t.s.a.)?
- If you no longer read r.a.t.s.a., when and why did you stop?
- What do/did you like most about r.a.t.s.(a.)?
- What do/did you like least about r.a.t.s.(a.)?
- In the time that you read/have been reading r.a.t.s. and/or r.a.t.s.a., what do you think are the most noticeable or important changes that have happened in the newsgroup?
- What do you think are some of the reasons why r.a.t.s.a. changed as it has?
- In the time that you read/have been reading r.a.t.s. and/or r.a.t.s.a., what has remained the same?
- What do you think are some of the reasons why these aspects of the group remained more stable over time?
- If you have been reading since the advent of the World Wide Web, how do you think this group has been changed by the Web?
- Do you maintain or visit Web sites related to this newsgroup? If so, please describe how your soap newsgroup and soap Web use are related.
- What types of relationships do you feel you have with other people who participate in this group?
- If you no longer read the group, have you maintained any relationships with people from the group? What types of relationships (if any) do you consider these to be?
- If you still are participating in r.a.t.s.a., how well do you think the term “community” fits this group now? Please explain why.
- How do you think you would have answered Question 13 when you first got to know this group?
- If you are not participating in r.a.t.s.a. anymore, how would you have answered Question 13 at the time you stopped?
- How (if at all) do you think participation in this newsgroup affects/affected your offline life?
- Do you have any other thoughts on this newsgroup, now or over time, that you would like me to consider?
- What is your age?
- What is your gender?
- What is your occupation?
Appendix B: Genre Analysis[Page 222]Method
To assess which genres were named in the subject line, I sampled 2 complete weeks of posts discussing All My Children (AMC). Drawing on a range of 41 weeks, I selected the week with the most traffic and the week with the least traffic from the weeks for which I had every single post. By selecting the 2 weeks with the broadest range, I expected to be able to see what genres appeared each week and also to gain preliminary insights into which genres contributed to the considerable difference in quantity between the 2 weeks. In the light week (ended September 7, 1992), there were 110 messages posted about AMC. In the heavy week (ended October 19, 1992), there were 280 messages about AMC. For each week, I looked at the subject lines, searching for indicants of category that were used by more than one person (either within the 2-week spans or elsewhere in the corpus). Because of the decision to look for genres open to more than one participant, the genre of FAQ (frequently asked questions) was excluded. I also calculated the number of responses to posts in each genre, recognizing that a response to a post within a genre might not itself be within that genre. For both sets of these categorizations, I calculated the number of posts in each genre, the number of lines in each genre, the average length of a post in each genre, and the percentage of the total posts and lines accounted for by each genre in each week. Despite the search for difference, the 2 weeks [Page 223]were proportionately nearly identical; only 3 of 14 categories differed by more than 5% of the total posts between the 2 weeks, and even those differences remained slight. Therefore, I combined the 2 weeks' results.Categories of Genre
These were the categories of genre. Their frequencies are tabulated in the table that follows.
Trivia. Trivia posts use the term “trivia” in the subject lines. These are posts that raised questions from AMC history in game form.
Unlurkings. Unlurkings, marked by the use of the terms “unlurking,” “unlurk,” and “lurker” in the subject lines, are posts in which new or rare posters introduce themselves to the group.
Sightings. Sightings, marked as such in the subject lines, are reports of having seen current or former soap opera actors in other contexts.
Spoilers. Spoilers, indicated with the word “spoiler” in the subject lines, involved the sharing of previews culled from magazines, sightings, and other computer networks.
Updates. Updates, marked by “update” and the shows' dates in the subject lines, are retellings of daily episodes.
Tangents. Tangents, marked by “TAN” in the subject lines, are a default category into which falls all discussions no longer directly related to the soap operas.
New threads. New threads are posts that first raise topics related to the soap opera. Subject lines usually identify the topics by character or characters (e.g., “AMC: Tad/Ted”) but can contain any of a range of components. The category of new threads includes many individual genres such as “predictions” (which guess at the shows' futures) and “comments” (which offer evaluations of the shows). None of these more precise genre titles is employed consistently in subject lines.[Page 224]TABLE B Genres of All My Children Posts
Appendix C: Analysis of Agreements and Disagreements[Page 225]Coding Procedures
I narrowed the data to a coherent but manageable subset by analyzing all the disagreements and agreements in the discussion of one story line on the soap opera All My Children (AMC). That story line was mentioned in 524 messages. An agreement initially was defined as any post that was explicitly responsive to a prior message and that took the same position as that message (although agreements could, and often did, go beyond stating that shared position). Disagreements were defined as those posts that were explicitly responsive to other messages and took positions incompatible with the prior messages. Disagreements were not necessarily directly contradictory but stated positions that could not logically be held if one held the prior positions.
In all but one case, agreements and disagreements were explicitly linked to prior messages through embedded quotations. Such quotations contained automatically generated reference lines indicating the prior writers and usually were edited down to the particular section to which the posts responded. These quotations with reference lines were used in all of the disagreements and in all but one of the agreements (which was linked through the phrase “as others have pointed out”). Thus, there could be no question that the authors of [Page 226]these messages were oriented to the prior turns. Although these posts also might have done more than agreed or disagreed, because they directly referenced and either affirmed or contradicted prior turns, they were considered to be agreements or disagreements. This is consistent with the notion that messages are multifunctional and that a single segment can involve multiple activities (O'Keefe, 1988).
A trained coder and I began by independently coding all of the messages about this story line as involving either agreement, disagreement, or neither. Disagreements between coders were resolved through discussion. The very few cases in which we could not agree on a post's status as agreement or disagreement resulted from ambiguous similarity or dissimilarity between the prior and posted positions. Those messages were not counted as agreements or disagreements. Of the 524 messages, most (77%) were categorized as “neither.” Of the remaining 121 messages, 70 (58%) were coded as agreements and 51 (42%) as disagreements. Thus, agreements constituted 13% of the total story line corpus, and disagreements constituted just under 10%.
Because posts often cover many topics, the disagreement and agreement responses often were only part of the posts. As in Mulkay (1985, 1986), the analyses presented here look only at the paragraphs immediately relevant to the topic of disagreement and agreement. I analyzed those sections of posts in which participants agreed or disagreed with previous positions, including all those components of speech that positioned messages as agreements or disagreements and those that framed these activities. Whereas this move pulls these responses from the full messages, it situates them in the temporal thread of talk in which they were embedded.
I developed a detailed coding scheme for these 121 segments by analyzing them repeatedly to determine which features appeared in multiple messages, a process that involved continual turning from data to categorical scheme, the latter being refined with subsequent rereadings of the former. The resulting scheme had 17 categories, 2 of which (quotation with reference and reference to another's talk) I have already discussed as methods of demonstrating explicit linkage to previous messages. The remaining 15 were: expression of the need to respond, other ways of linking to a prior message, explicit indication of agreement or disagreement, assertion that affirmed or contradicted the prior message, partial agreement, qualifier, elaboration, provision of reasoning, expression of gratitude to the previous poster, apology, explicit acknowledgment of the other's position, use of the other's name, smiley face(s), framing as nonoffensive, and a catch-all “other” category. I will elaborate on these categories in a moment.
Once this scheme had been generated, the agreements and disagreements were coded for each feature separately by each coder. Messages were coded for the presence or absence of each component rather than for quantity or sequential [Page 227]ordering (although at times sequences were apparent). There were several differences in our initial codings. To some extent, this was due to misunderstandings about the definitions of the categories. In other cases, this resulted from difficulties in distinguishing among categories (this was especially true of separating reasoning from elaboration). In some cases, the problems stemmed from focusing on different agreement or disagreement responses within the same posts. However, despite our initial divergences, we were able to resolve our coding differences remarkably easily, and there were no cases in which we still disagreed after discussing the logic of our choices. Although this categorical scheme is not the only way in which one could analyze the message components of these posts, it did account for nearly all of the agreement- or disagreement-relevant segments. Only 8 messages contained a message component categorized as “other.”Message Components of Agreements and Disagreements
Topics of Agreements and Disagreements
- Expression of the need to respond: Phrases such as “I had to reply to your post” that framed the author's post as necessary
- Other ways of linking to a prior message: References to prior talk such as “we've talked about this already”
- Explicit indication of agreement or disagreement: Use of the phrase “I agree” and strong agreement tokens such as “indeed” and “you said it,” or use of the word “disagree” or its synonyms and disagreement tokens such as “but”
- Assertion that confirms or contradicts the prior message: Assessment that affirms or contradicts the claim of the quoted message; considered an indicator of the presence of agreement or disagreement
- Partial agreement: Phrases such as “I thought so too” followed by disagreement tokens such as “but” and “though” or phrases such as “at the same time” positioning what followed as disagreement
- Qualifier: “I think that,” “that's only my opinion,” and other phrases that lessened the extent to which the speaker could be held accountable for the veracity of a post's content (Goffman, 1981)
- Elaboration: Extension of the talk from the immediate agreement or disagreement to a new but related angle or topic; operationalized as anything that made more sense as the second half of the sentence “I agree with the quoted utterance and …” than as the second half of the sentence “I agree with the quoted utterance because …” [Page 228]
- Provision of reasoning: Presentation of a rationale to support the writer's perspective; operationalized as anything that made more sense as the second half of the sentence “I agree with the quoted utterance because …” than as the second half of the sentence “I agree with the quoted utterance and …”
- Expression of gratitude to the previous poster: Phrases such as “thank you for your post”
- Apology: Use of the phrase “I'm sorry”
- Explicit acknowledgment of the other's position: Phrases such as “I see your point” and “I know what you mean.”
- Use of the other's name: Using the first name of the quoted poster
- Smiley face(s): Socioemotional cue built out of punctuation marks—usually a colon, a hyphen, and a right parenthesis:-)
- Framing as nonoffensive: Explicitly framing the post as nonconfrontational (e.g., “no offense”)
Many of the agreements and disagreements dealt with more than one topic simultaneously. A total of 71 agreements and disagreements involved only one topic, 25 involved two topics, 20 involved three topics, 4 involved four topics, and 1 involved five topics.Factual Topics
- Narrative events: Retellings of what happened on the show
- Sighting: Posts about seeing a soap opera actor in another role or at a personal appearance
- Character psyches: Interpreting the meaning of characters' behavior
- Realism: Assessing how (un)realistic the show's events are
- Emotional reaction: Explicitly sharing one's own emotional responses to the show's events
- Story line suggestions: Projected story lines that the posters would like to see, which might or might not be what the posters think actually will happen [Page 229]
- Story line worth: Evaluating the story line as a whole
- Ideological messages: Evaluating the social value of the representations constructed in the story text
- Character worth: Evaluating the overall quality of individual characters
- Genre preference: Evaluating normatively what a soap opera should show using the posters' own pleasures as the criteria
- Dialogue: Assessing the quality of the writing of the show
- Story line influence: Assessing what other stories might have influenced the soap opera writers in constructing the story line
- Actor appearance: Evaluating how the actors look
- Crossover: The crossover between AMC and Loving
- Soap quality: Assessing the quality of the soap opera Loving
- Directing: Assessing the quality of AMC's directing
- Actor input: The extent to which the actor had creative input into the writing of the character
- Sets: The use and reuse of sets, in particular, a recognizable cabin used earlier
- Narrative device: Whether or not one needed an invitation to attend a party on a soap opera (one does not)
TABLE C Frequency of Topics in Disagreements and Agreements Activities Total Posts and Percentage Factual Narrative events 13(11) Sighting 3(2) Interpretive Character psyche 53(44) Realism 20(17) Emotional reaction 20(17) Story line suggestion 15(12) Story line worth 14(12) Ideological worth 13(11) Character worth 13(11) Acting 13(11) Genre preference 7(6) Dialogue 4(3) Story line influence 3(2) Actor appearance 3(2) Soap crossover 2(2) Soap quality 2(2) Directing 1(1) Actor influence 1(1) Sets 1(1) Narrative device 1(1)NOTE: Percentages are in parentheses. Percentages total more than 100 because they indicate what proportions of the agreements and disagreements addressed each topic. Several of the messages contained more than one topic and, therefore, are counted more than once.
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About the Author[Page 249]
Nancy K. Baym is Assistant Professor of Communication Studies at the University of Kansas, where she teaches courses in computer-mediated communication and interpersonal communication. She earned her doctorate in speech communications at the University of Illinois at Urbana-Champaign in 1994.