CMDA Syllabus

S641: Computer-Mediated Discourse Analysis


Spring 2014


Susan Herring and Guo Zhang


Monday 5:45-8:30 p.m.


Wells Library 037


LI 030


(812) 856-4919




herring @; guozhang @

Instructors' Office Hours: Herring - M & Th 4:15-5:15 p.m.; Zhang - M 10-11 a.m. or by appointment

Facebook group (for class members only): Z641: CMDA

Required Reading:


The required readings for each week are listed in the Course Schedule at the end of this syllabus. Articles not accessible on the public web will be made available electronically on Oncourse.

1.   Course Description

Computer-mediated discourse (CMD) is human-to-human communication carried out over computer networks or wireless technologies; it is produced by typing, speaking, or other means. It is the discourse that takes place via computer-mediated communication (CMC) technologies such as chat, text messaging, email, mailing lists, web boards, blogs, microblogs, wikis, virtual worlds, social network sites, and other digital media. Computer-Mediated Discourse Analysis (CMDA) is a set of methods grounded in linguistic discourse analysis for mining CMD for patterns of structure and meaning. CMDA methods can also be used to extract indirect evidence of socio-cognitive phenomena related to networked communication, such as collaboration, disinhibition, engagement, identity, power dynamics, and trust.

This is a methodology course. It provides practical training and hands-on experience in applying computer-mediated discourse analysis methods (no previous knowledge required), in designing research that make use of such methods, and in interpreting their results. The focus of the course is on micro-analytic, quantitative methods. Systems for visualizing and automating the analysis of computer-mediated discourse are also presented.

2.   Course Objectives

The primary goal of this course is to provide training in applying a set of empirical analytical methods to computer-mediated discourse. A broader goal is to instill an understanding of the CMDA process that will enable you to design and carry out your own CMDA research, and to modify the methods or devise new methods as needed to address questions and data of interest to you.

Specifically, as a result of completing this course, you should be able to:

  descriptively classify a variety of CMC types

  apply discourse analysis methods to analyze participation, structure, meaning, interaction, and social behavior in CMD

  design and carry out an original CMDA research project that captures the nitty-gritty of language use, but also relates it to some broader phenomenon (e.g., social forces, community factors, cognitive/behavioral effects)

3.   Student Requirements

The assigned readings are to be completed before class each week. You will not be tested on the readings or be asked to keep notes on them, but you will be expected to apply concepts and techniques from them, so it is important that you read and understand them fully.

There will be four oral and written reports during the semester in which you will apply methods of discourse analysis from the readings and the class lectures to a sample of computer-mediated data of your choice and report on your findings. The oral reports will be brief, about 5 minutes in length, and will require you to be selective in your presentation of findings. The written reports, which are due one week after the oral reports, should be 3-4 typed pages long, excluding appendices. The written reports will follow the same guidelines as the oral reports, only your presentations of findings should be more complete. Specific guidelines for each report will be posted at least one week before the oral reports are scheduled to be presented.

The best kind of data to analyze for the reports is one continuous log of interactive, text-based CMD.
It is normally expected that you will use the same sample for all fouorts. An appropriate sample size for asynchronous (email-type) CMD is 40-100 messages, depending on the length of the messages. For synchronous (chat-type) CMD, an appropriate sample size is about half an hour of chat or 200 messages, whichever is longer. You should collect and store more data from your source than you will need for the purposes of the reports, as a backup. We will discuss possible sources of data in more detail during the first class meeting.

The major requirement for the course is a research paper, due at the end of the semester, analyzing in depth some feature or features of computer-mediated discourse in data of your choice. The data may or may not be of the same type as you analyzed for the reports throughout the semester. They may include the sample you already analyzed, plus additional data as determined by the nature of your research question(s), or you may analyze a new sample. The written paper should be in the range of 4000-7000 words long, not counting references and appendices, and should follow the conventions for a publishable-quality research article, including footnotes and citations of scholarly work in APA (American Psychological Association) style. For examples of APA conventions, see articles in the Journal of Computer-Mediated Communication  (

The last two weeks of the course will be devoted to conference-style oral presentations (15-20 minutes, depending on the number of students enrolled) of your term paper research to the rest of the class.  You will be expected to prepare PowerPoint slides for all oral presentations.

4.   Student Evaluation

Your final grade in the course will be calculated as follows:


Attendance and participation
Oral reports (4 x 4%)                       


Written reports (4 x 6%)


Oral presentation of term paper


Term paper




Grading Policy

    A late written report will be accepted once during the semester, no questions asked, provided it is turned in two days before the next class meeting, to allow me time to grade it. I reserve the right to subtract one-third of a letter grade (from A to A-, A- to B+, etc.) for each day a report is late beyond the due date or this one-time extension. This penalty also applies to the final paper.

    Class participation means speaking in class in an informed way about the topics under discussion. A good rule of thumb is to try to speak at least twice in each class session. In order to be able to speak intelligently about a topic, you will need to have done the readings for that topic before class. You will also need to be physically present and attentive (e.g., NOT surfing the Web or reading email). Participation cannot be made up if you miss a class.

    Oral reports will be graded with a check mark to indicate a satisfactory presentation. A satisfactory presentation is one that makes a good faith effort to address all the questions in the guidelines given in advance for each report, even if the report contains some errors. This method of grading is intended to encourage you to try to apply the methods, even if you feel somewhat uncertain how to do so.

    Written reports, the oral presentation of your term paper research, and the written term paper will be assigned letter grades (A, A-, B+, B, B-, C+, C, etc.). A composite grade such as A-/B+ means that the grade is between an A- and a B+ (i.e., 89.5%). Grades in the 'A' range indicate outstanding work. Grades in the 'B' range indicate very good to good work. Grades in the 'C' range indicate average work, and a grade of 'D' or below is poor work.  Graduate students are expected to perform at a 'B' level or above.

    Written reports should be concise (3-4 typed pages) and written in continuous prose (NOT outline style). Elaborate introductory and concluding paragraphs are unnecessary, but each report should begin with a statement of the topic that the report will address and should be sure to answer explicitly all questions asked in the guidelines for the report. DO include examples from your data and/or summary tables and graphs of your analytical results in your report, to support your claims. If including these supporting materials in the report would disrupt its flow, they may be appended to the report as an appendix. An 'A' quality written report is written clearly and concisely, answers all the questions asked, applies the methods correctly, and interprets the results plausibly and convincingly.

    The oral presentation of your term paper research will be graded primarily on form: how well it is organized, how informative it is, and how clearly and professionally it communicates to your audience (i.e., the rest of the class). An 'A' quality oral report conveys an appropriate amount of information given the time allotted for the presentation, is presented in a clear and concise manner, and is logically organized (usually following the schema: identification and motivation of your research question, brief background, data sample and methods of analysis, your findings, and some interpretation of the findings).

    The written term paper will be evaluated on content, including the quality of the project design—originality of the research question, appropriateness of the data and methods used to investigate the question, plausibility of your interpretations—and form—organization (similar to that for oral presentations), clarity and quality of written expression, and appropriate use of scholarly conventions such as citations and footnotes. An 'A' quality term paper addresses an interesting research question, makes use of an appropriate empirical method to address the research question(s), applies the method(s) systematically, and interprets the findings thoughtfully, in addition to being well-organized and clearly and professionally written.

Academic honesty:  Most of your activity in this course will involve producing original research. However, in writing about your research, and especially in your final paper, it may be necessary to reference previous work. As a rule of thumb, when in doubt, cite the source! In accordance with the policies of Indiana University, plagiarism, copyright infringement, and other types of academic dishonesty will not be tolerated. To help you recognize plagiarism, the IU Writing Center has prepared a short guide: Plagiarism: What It is and How to Recognize and Avoid It (

5. Tentative Course Schedule

(Under construction! Check back regularly for updates.)


Week 1 (1/13):

Introduction to the course. Nature and classification of computer-mediated discourse. Selecting data for analysis. Getting approval from the Human Subjects Committee (HSC) to conduct your research.


1. Herring, S. C. (2001). Computer-mediated discourse. In D. Schiffrin, D. Tannen, & H. Hamilton (Eds.), The Handbook of Discourse Analysis (pp. 612-634). Oxford: Blackwell Publishers.

2. Herring, S. C. (2007). A faceted classification scheme for computer-mediated discourse. Language@Internet, 4, article 1.



Week 2 (1/20):


Collect your initial data sample.


Herring, S. C. (2013). Discourse in Web 2.0: Familiar, reconfigured, and emergent. In D. Tannen & A. M. Tester (Eds.), Georgetown University Round Table on Languages and Linguistics 2011: Discourse 2.0: Language and new media (pp. 1-25). Washington, DC: Georgetown University Press.

Finish reading articles from Week 1 if you haven't already.


Take the Human Subjects Protection test at:



Week 3 (1/27):

CMDA as empirical social science. Data sampling and management.

Submit request for HSC approval (if required to do so by the nature of your data).

In class: Describe the type of interactive, text-based CMC you will analyze in this course. Classify it in terms of key medium and situation variables as presented in Herring (2007).


1. Herring, S. C. (2004). Computer-mediated discourse analysis: An approach to researching online behavior. In S. A. Barab, R. Kling, & J. H. Gray (Eds.), Designing for virtual communities in the service of learning (pp. 338-376). New York: Cambridge University Press.

2. Marcoccia, M., Atifi, H., & Gauducheau, N. (2008). Text-centered versus multimodal analysis of instant messaging conversation. Language@Internet, 5, article 7.

3. Androutsopoulos, J. (2008). Potentials and limitations of discourse-centred online ethnography. Language@Internet, 5, article 8.


Week 4 (2/3):

Analyzing participation and word use.


1. Herring, S. C., Johnson, D. A., & DiBenedetto, T. (1998). Participation in electronic discourse in a 'feminist' field. In: J. Coates (Ed.), Language and Gender: A Reader (pp. 197-210). Oxford: Blackwell. [Oncourse]

2. Ko, K-K. (1996). Structural characteristics of computer-mediated language: A comparative analysis of InterChange discourse. Electronic Journal of Communication/Revue électronique de communication, 6(3). [Oncourse]

3. Schwartz, H. A., Eichstaedt, J. C., Kern, M. L., Dziurzynski, L., Ramones, S. M., Agrawal, M., Shah, A., Kosinski, M., Stillwell, D., Seligman, M. E. P., & Ungar L. H. (2013). Personality, gender, and age in the language of social media: The open-vocabulary approach. PLOS ONE, September 25.

Demo: LIWC


Week 5 (2/10):

Analyzing linguistic structure.

1st Oral Report: Basic descriptive statistics about your data: Participation and word frequencies.


1. Herring, S. C. (2012). Grammar and electronic communication. In C. Chapelle (Ed.), Encyclopedia of applied linguistics. Hoboken, NJ: Wiley-Blackwell.

2. Page, R. (2012). The linguistics of self-branding and micro-celebrity in Twitter: The role of hashtags. Discourse & Communication, 6(2), 181-201. [Oncourse]


Week 6 (2/17):

Analyzing meaning: Speech acts.

1st Written Report due: Basic descriptive statistics about your data: Participation and word frequencies. What do they reveal?


1. Nastri, J., Peña, J., & Hancock, J. T. (2006), The construction of away messages: A speech act analysis. Journal of Computer-Mediated Communication, 11, 1025–1045.

2. Herring, S. C., Das, A., & Penumarthy, S. (2005). CMC act taxonomy. [short]

3. Kapidzic, S., & Herring, S. C. (2011). Gender, communication, and self-presentation in teen chatrooms revisited: Have patterns changed? Journal of Computer-Mediated Communication, 17(1), 39-59. [focus on results of textual analysis]

Practice coding speech acts in class.



Week 7 (2/24):

Analyzing meaning: Functional moves and schemas.

2nd Oral Report: Acts in your data sample.


1. Herring, S. C. (1996). Two variants of an electronic message schema. In S. Herring (ed.), Computer-mediated communication: Linguistic, social and cross-cultural perspectives (pp. 81-106). Amsterdam: John Benjamins. [Oncourse]

2. Condon, S. L., & Cech, C. G. (1996). Functional comparisons of face-to-face and computer-mediated decision making interactions. In S. C. Herring (Ed.), Computer-mediated communication: Linguistic, social and cross-cultural perspectives (pp. 65–80). Amsterdam: John Benjamins. [Oncourse]

Practice interrater reliability assessment in class.


Week 8 (3/3):

Analyzing conversational interaction: Topic development.

2nd Written Report due: Acts in your data sample. What kinds of communicative activities are the participants engaged in?


1. Herring, S. C. (2003). Dynamic topic analysis of synchronous chat. In: New Research for New Media: Innovative Research Methodologies Symposium Working Papers and Readings. Minneapolis, MN: University of Minnesota School of Journalism and Mass Communication. [Oncourse]

2. Herring, S. C., & Kurtz, A. J. (2006). Visualizing Dynamic Topic Analysis. Proceedings of CHI'06. ACM Press.

3. Honeycutt, C., & Herring, S. C. (2009). Beyond microblogging: Conversation and collaboration via Twitter. Proceedings of the Forty-Second Hawai'i International Conference on System Sciences (HICSS-42). Los Alamitos, CA: IEEE Press.

Demo: VisualDTA


Week 9 (3/10):

Interaction analysis (cont.): Turn-taking and coherence.

3rd Oral Report: Topic development in your sample.


1. Herring, S. C. (1999). Interactional coherence in CMC. Journal of Computer-Mediated Communication, 4 (4).

2. Anderson, J. F., Beard, F. K., & Walther, J. B. (2010). Turn-taking and the local management of conversation in a highly simultaneous computer-mediated communication system.Language@Internet, 7, article 7.





Week 10 (3/24):

Analyzing social behavior: Politeness and conflict.

3rd Written Report due: Topic development and coherence in your sample.


Come to class prepared to discuss term paper research ideas.


1. Brown, G. & Levinson, S. (1987).  Politeness: Some Universals in Language Usage (pp. 59-84). Cambridge University Press. [Oncourse]       

2. Herring, S. C. (1994). Politeness in computer culture: Why women thank and men flame. In M. Bucholtz, A. Liang, L. Sutton, & C. Hines (Eds.), Cultural Performances: Proceedings of the Third Berkeley Women and Language Conference (pp. 278-94). Berkeley: Berkeley Women and Language Group. [Oncourse]

Practice politeness coding in class.


Week 11 (3/31):

Voicing: Intertextuality, performativity, and heteroglossia.

Turn in a 500-word proposal for term paper research, describing your topic, research question, data, methods, preliminary observations, and including at least five relevant references.


1. Hodsdon-Champeon, C. B. (2010). Conversations within conversations: Intertextuality in racially antagonistic online discourse. Language@Internet, 7, article 10.

2. Virtanen, T. (2013). Performativity in computer-mediated communication. In S. C. Herring, D. Stein, & T. Virtanen (Eds.), Handbook of the pragmatics of computer-mediated communication. Berlin: Mouton de Gruyter.

3. Androutsopoulos, J. (2011). From variation to heteroglossia in the study of computer-mediated discourse. In C. Thurlow & K. Mroczek (Eds.), Digital discourse: Language in the new media (pp. 277–298). New York: Oxford University Press. [Oncourse]


Week 12 (4/7):


Automating CMDA.

4th Oral Report: Politeness and conflict in your sample.

1. Bender, E. M., Morgan, J. T., Oxley, M., Zachry, M., et al. (2011). Annotating social acts: Authority claims and alignment moves in Wikipedia talk pages. Proceedings of the Workshop on Language in Social Media (LSM 2011) (pp. 48–57), Portland, Oregon, June 23. [Oncourse]

2. Xu, J-M., Jun, K-S., Zhu, X., & Bellmore, A. (2012). Learning from bullying traces in social media. 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (pp. 656–666), Montreal, Canada, June 3-8. [Oncourse]

3. Raz, Y. (2012). Automatic humor classification on Twitter. Proceedings of the NAACL HLT Student Research Workshop (pp. 66-70), Montreal, Canada, June 3-8. [Oncourse]


Week 13 (4/14):


Multimodal CMD.

4th Written Report due: Politeness and conflict in your sample.

1. Jucker, A. H. (2010). Audacious, brilliant!! What a strike! Live text commentaries on the Internet as real-time narratives. In C. R. Hoffmann (Ed.), Narrative revisited: Telling a story in the age of new media (pp. 57-77). Amsterdam: John Benjamins. [Oncourse]

2. Sindoni, M. G. (2011). “Mode-switching”: Speech and writing in videochats. Paper presented at the Georgetown University Round Table on Languages and Linguistics, Washington, DC, March 11. [Oncourse]

3. Newon, L. (2011). Multimodal creativity and identities of expertise in the digital ecology of a World of Warcraft guild. In C. Thurlow & K. Mroczek (Eds.), Digital discourse: Language in the new media (pp. 203-231). NY: Oxford University Press. [Oncourse]


Week 14 (4/21):

CMD in other languages and other cultures.


(Choose 3)

1. Bieswanger, M. (2007). 2 abbrevi8 or not 2 abbrevi8: A contrastive analysis of different shortening strategies in English and German text messages. Texas Linguistics Forum 50.

2. Vaisman, C. (2013). Beautiful script, cute spelling and glamorous words: Doing girlhood through language playfulness on Israeli blogs. Language & Communication, 34, 69-80. [Oncourse]

3. Panyametheekul, S., & Herring, S. C. (2003). Gender and turn allocation in a Thai chat room. Journal of Computer-Mediated Communication, 9(1).

4. Kaul, A., & Kulkarni, V. (2005). Coffee, tea, or . . . ? Gender and politeness in computer-mediated communication (CMC). Indian Institute of Management Ahmedabad Working Papers.

5. Georgakopoulou, A. (1997). Self-presentation and interactional alliances in e-mail discourse: the style- and code-switches of Greek messages. International Journal of Applied Linguistics, 7(2), 141-162. [Oncourse]


Week 15 (4/28):

Oral presentations


Week 16 (5/5):

Final papers due MONDAY, MAY 5 at 6:00 p.m.

Last updated: 1/31/14