Illinois Technical Report No. 2007020 Link to the PDF.

To build marketing strategy, face-to-face focus group discussion has been one of the reliable approaches for collecting variety of ideas and opinions for long years. Although various network-based communication tools have been available, on-line focus group discussions have not been popular yet. This is due to complications in facilitation of on-line discussions. The facilitators have to observe and control the discussions carefully and skillfully, which is far more difficult on on-line than on off-line. The goal of this paper is to maximize the profit from on-line focus group discussions by supporting facilitators’ task. We suppose that the on-line discussion is a discussion that are done by posting and replying messages on on-line threaded discussion board. First, we propose a message feature map and two metrics for measuring message feature; centrality and novelty. The message feature map plots discussion messages on centrality-novelty plane, and gives us intuitive understanding of the discussions in various aspects. Then, reporting experimental results by using real data collected in on-line focus group discussions, we discuss how we can utilize the message feature map for the effective facilitation.

Illinois Technical Report No. 2007021 Link to the PDF.

This paper focuses on the online discussions done by exchanging text based messages on online message boards. The goal of this paper is to delineate discussion topics and enhance understanding discussants message features. Toward this goal, first, we propose a method for extracting important messages and terms from discussions. This method is based on a well-know link analysis algorithm, HITS. Next, we propose a message feature map, which is visualization of messages plots on a plane with the axes; centrality and novelty. Then, we classify message characteristics into four types on the message feature map, and describe a message feature transition graph. We also examine how our approaches can be used on real world setting by using data obtained by online focus group discussions. The experimental results indicate that our approach gives us intuitive understanding of the discussion topics and the message features, and helps us to identify the messages that should be focused on from the marketing view point.

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Illinois Technical Report No. 2006026 Link to the PDF.

The blogsphere is a valuable source of information. From simple topic analysis in the blogosphere—what’s hot—to harvesting and analyzing valuable market trends—what product and features are suggested—require a tight integration of computer- and human-based analysis capabilities. Computers can easily assist the processing filtering and visualizing relevant and key elements of the blogosphere, but coupling them with human evaluation and reasoning can provide the final steps to connect pieces of relevant information into better description map of the current trends of the blogosphere. An example of the need for such human-centered analysis was David R. Ellis’ film Snakes on a Plane (2006) which failed to properly translate blogosphere discussions into a successful commercial product—as a clear misalignment of both environments the blogsphere and the final targeted market. In this paper, we present some human-centered visualization and analysis tools that can help users to compare and reason synergies and misalignments revolving around a particular topic.

Illinois Technical Report No. 2006025 Link to the PDF.

In this paper, we propose some methodologies for delineating topic and discussant transitions in online collaborative environments, more precisely, focus group discussions for product conceptualization. First, we propose KEE (Key Elements Extraction) algorithm, an algorithm for simultaneously finding key terms and key persons in a discussion. Based on KEE algorithm, we propose approaches for analyzing two important factors of discussions: discussion dynamics and emerging social networks. Examining our approaches using actual network-based discussion data generated by real focus groups in a marketing environment, we report interesting results that demonstrate how our approaches could effectively discover knowledge in the discussions.

Illinois Technical Report No. 2006024 Link to the PDF.

This paper proposes AKEE (Adaptable Key Elements Extraction) algorithm for web-log (blog, for short) mining. AKEE enables us to identify significant information in various blog components (e.g., a blog post, a series of blog posts, a set of series of blog posts, etc.).

Illinois Technical Report No. 2006023. Link to the PDF.

Blogging has become a new and disruptive communication medium. Blogs have changed the way people and organizations express, interact, and—quite unforeseen—exercise influence. The digital nature of the blog media provides access to an always-expanding corpus of information. It would take more than a lifetime to read all the available blogs necessary to answer questions such as what were the more relevant plots suggested or what key concepts were managed by bloggers in their ideas. However, human-centered analysis and visualization techniques may help users navigate such enormous corpus. This paper presents human-centered analysis and visualization techniques for supporting innovation and creativity can help to identify relevant post portions and to visualize concept relations in the blogosphere.

We have not stopped at reengineering the DISCUS site. We have also created an extension for Firefox that allow you to analyze the web page you are currently viewing. All DISCUS capabilities integrated in your browser. The DISCUS Firefox extension adds a DISCUS toolbar, some entries on the tools menu and in the right-click contextual menu. Hope you find it useful. Following the site, this toolbar will also grow and incorporate new features and human-centered analytic tools.