What Does a Very Large-Scale Conversation Look Like? (sidebar)

What Does a Very Large-Scale Conversation Look Like? (sidebar)

Warren Sack

Text and full-size sidebar images from “What Does a Very Large-Scale Conversation Look Like?”


In the following section I show twelve example Conversation Maps that were generated from a wide variety of online public discussions. With these examples, I hope the semiotics of how to read these maps will become understandable. Also I hope that these one page, graphical summaries of hundreds or thousands of e-mail messages will be seen to be a useful thing for gaining a quick glimpse into a very large-scale conversation.


17.3a. Before the election.

The map above and the map below were created about a week apart using messages from the newsgroup alt.politics elections. The map above (figure 17.3a) was generated immediately before the 2000 presidential election. Notice how the main themes of discussion center around the candidates: Gore, Bush, and Nader. A week after the election the conversation (as mapped below, 17.3b) has moved away from a discussion of the candidates. Now it is a discussion of the technicalities of elections: votes, counts, ballots, laws, and courts are the newly prominent themes of discussion.

17.3b. After the election.


17.4a. Talking to one another.

This pair of maps (17.4a, 17.4b) show the same newsgroup (a discussion about the television show The X-Files) at two different times. Notice how many themes of discussion there are in the map above. Now, notice how very few themes of discussion are listed in the map below. Because the Conversation Map uses a very generous means of counting the themes of dicussion, it usually lists too many, not too few. What this map tells us is that no one is following up on what other people are saying. The two snapshots in time represented by these two maps demonstrate how an online discussion can change from being one where people talk to one another into one where they just talk at one another. This fact is also represented in the very scattered appearance of the social network.

17.4b. Talking at one another.


17.5a. People as problems.

The map above (17.5a) represents about a month’s worth of messages posted to the group sci.environment. The map below (17.5b) represents the same newsgroup one month later. By comparing the two maps you can get some idea of how the group has changed over time. One thing that has remained stable between the two maps is the connection in the semantic networks between the terms “people” and “problem.” This is a clue that perhaps, in this newsgroup, people are seen to be one of the main causes of environmental problems. But a hypothesis like this that one can come up with by looking at the maps needs further investigation to be confirmed or discarded.

17.5b. And, problems as people.


17.6a. A shallow conversation.

Above (17.6a) is a map of about 300 messages from the Usenet newsgroup misc.education. Note the themes of discussion and compare them to the map on the right. Both maps summarize discussions about education and learning. The map below (17.6b) summarizes a semester’s worth of messages posted by a distance learning course taught by Prof. Linda Polin of Pepperdine University. In comparison with the first map, note how much more tightly knit the social network is here: people are responding to one another. Note also the elaborate threads containing many messages as compared to the sparse threads in the first map. These elaborate thread structures show that the participants are repeatedly elaborating on one another’s posting. This sort of an exchange is perhaps much deeper than, for example, the quick question-and-answer format of the technology discussions depicted below and the curt exchanges that one can note in the threads of the political discussions above.

17.6b. A deep conversation.


17.7a. Experts as hubs in a social network.

The conversation map above (17.7a) was created from about a month’s worth of messages posted to a public listserv devoted to the construction of Lego robots. Note how the social network shows that there are multiple hubs: these correspond to an expert in mechanical systems, an expert in programming, and expert in electronics. The second map (17.7b) is an analysis of about 2500 messages from the newsgroup devoted to the Perl programming language: comp.lang.perl.misc. Note the dense social network and also compare the thread pattern here with the class-based, education conversation analyzed above. The pattern here is indicative of a series of brief question-answer clusters. The elaborate threads above indicate that participants are repeatedly elaborating on one another’s responses.

17.7b. A pattern of question-answer pairs.


17.8a. Illness and family relations.

The conversation depicted in figure 17.8, above (17.8a), took place in a public newsgroup devoted to attention-deficit disorder. However, one can see from the map that the discussion was not just about the illness, but about family members as well. The map below (17.8b) is summary of several hundred messages sent to a newsgroup on chronic-fatigue syndrome. As can be seen here too, the discussion focuses – not just on the illness – but on a more general discussion of people and citizenry. The anthropologist of science, Prof. Joseph Dumit of MIT, argues that illness like these (ADD and CFS) are illnesses one has to “fight to get” because they are often not recognized by doctors and insurance companies. Consequently, online discussions can become places where sufferers can meet and illness-based social movements can emerge.

17.8b. Illness and citizens

back to What Does a Very Large-Scale Conversation Look Like?