Follow the Reader: Filtering Comments on Slashdot
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Follow the Reader: Filtering Comments on Slashdot Cliff Lampe Erik Johnston, Paul Resnick Michigan State University University of Michigan Communication Arts and Sciences School of Information East Lansing, MI 48824 Ann Arbor, MI 48109 [email protected] {erikwj, presnick}@umich.edu ABSTRACT discovery [7] and political discourse [13]. However, users Large-scale online communities need to manage the tension may never realize these positive outcomes if worthwhile between critical mass and information overload. Slashdot content is buried in the rush of messages typical in online is a news and discussion site that has used comment rating discussions involving hundreds or thousands of to allow massive participation while providing a participants. Additionally, many online systems currently mechanism for users to filter content. By default, depend on persistent user identity and customization to comments with low ratings are hidden. Of users who operate over time. Sites like Flickr, Wikipedia and changed the defaults, more than three times as many chose YouTube, sometimes referred to as Web 2.0 sites, depend to use ratings for filtering or sorting as chose to suppress on mixes of anonymous and registered user interactions. the use of comment ratings. Nearly half of registered users, This work addresses how to leverage the choices made by however, never strayed from the default filtering settings, some users to improve the interfaces of all users. suggesting that the costs of exploring and selecting custom filter settings exceeds the expected benefit for many users. Information overload occurs when an individual is unable We recommend leveraging the efforts of the users that to process or use all of the available inputs. Early research actively choose filter settings to reduce the cost of changing in psychology showed that humans have a limited cognitive settings for all other users. One strategy is to create static capacity to accept new information [18]. This limitation is schemas that capture the filtering preferences of different exacerbated in CMC settings where barriers to receive groups of readers. Another strategy is to dynamically set information are reduced through the use of computing filtering thresholds for each conversation thread, based in systems. part on the choices of previous readers. For predicting later Jones et al. [11] examined Usenet newsgroups and found readers’ choices, the choices of previous readers are far that users are more likely to respond to simpler messages in more useful than content features such as the number of situations of overload; that users will end participation as comments or the ratings of those comments. overload increases and that users generate simpler responses as overload increases. Jones and Rafaeli [12] Author Keywords also found that in larger Usenet newsgroups, as measured Social navigation, virtual community, computer-mediated by number of postings to the group, messages became communication, recommender systems. shorter. Previously, Jones and Rafaeli [10] proposed that communication online takes an S-shaped pattern of ACM Classification Keywords frequency of occurrence. Early in the existence of a H5.m. Information interfaces and presentation (e.g., HCI): conversation space, or “virtual public” to use their term, Miscellaneous. there is a struggle to achieve critical mass of people contributing to the conversation. A sharp increase after that INTRODUCTION critical mass is achieved results in information overload, Massive, many-to-many online discussions may have a and communication levels off as participants are dis- range of benefits, including information sharing [1], the incentivized by the rate of messages. Jones and Rafaeli creation of new forms of social capital [20], scientific [12] have described this as a tension between the critical mass needed to benefit from “shared public online interpersonal interactions” and the breakdowns that occur in information overload conditions. Butler [3] found that large listservs lost a higher proportion of their users to attrition than smaller groups. Too few interactions and nothing may result, but too many and results are lost in the noise. 1 Several strategies have been employed to help readers make environment more aesthetically pleasing was generally sense of complex online environments. Netscan provides avoided. Mackay concluded that users “satisfice” rather statistics and visualizations about Usenet participation, than optimize; that is, they do the minimum necessary to helping to illustrate newsgroup interaction dimensions and use the software. styles [23]. Visualizations have also been used to provide Page et al. [19] studied 101 users of a text-editing program context to email discussions [8], Wikipedia interactions and found that 92% of participants did some form of [25] and cross-linking in blogs and personal Web pages [2]. customization. They also found a strong relationship Ackerman [1] has used a combination of software agents, between how much the software was used and the amount social rules and automatic text summarization to “distill” of customization that took place. The more the system was comments from an online discussion forum into discrete used, the more customization users engaged in. This discussion summaries. research suggests that users only change options when Rating systems have been used widely to provide absolutely necessary, for instance when their work is being information about people, products and content online [24]. seriously impeded, or they are heavy users and find certain An early attempt to apply ratings to online messages was repetitive tasks easier to customize. Mackay mentions the Tapestry [9] system, which had users rate content in an satisficing as a possible explanation for this behavior. intranet messaging site, and then made recommendations Satisficing is a term from Simon [22], and relates to the for new articles based on collaborative filtering strategies. bounded capacity for humans to make rational decisions. GroupLens [21] applied this idea to Usenet and introduced Cognitively, people are unable to hold all the variables the technique of automated, personalized recommendations necessary for making an optimal choice in mind, so they based on the ratings of people with similar tastes, a instead choose a “good enough” solution. March and technique that is now commonly referred to as collaborative Simon [17] argue that only in rare occasions are people filtering or recommender systems. GroupLens displayed its concerned with the optimal solution, and that people predictions of user interest in a message as a guide, but did compare the marginal-benefit of making a decision with the not automatically use the predictions to sort or filter cost of that decision in terms of risk. messages. Consequently, we must be circumspect in making Slashdot, a popular news and commentary site, collects inferences about the preferences of readers who have not ratings from selected readers who act in a “moderator” role. made changes to the default settings. Our approach is to Moderators assign labels such as “Informative”, “Funny”, focus on lead users, those who have made explicit choices or “Troll” to comments. Based on those labels, each about their viewing settings. We extrapolate from the comment accumulates a score from -1 to +5. Slashdot not revealed preferences of those lead users to infer what other, only displays the score of each message, but also allows less proactive users, might like the system to do, if there users to sort or filter the available messages based on those were no friction preventing them from telling the system scores. Previous papers have examined both successes and what to do. limitations in the provision of ratings for messages at Slashdot [15] and the impacts that ratings have on writers VIEWING SLASHDOT COMMENTS [14]. The default view for comments in a Slashdot forum is a threaded structure with a filtering “threshold” of +1. This Here, we examine the impact of ratings on readers. First, means that at the top level, comments rated +1 or above are we look for evidence about whether users prefer that ratings shown with their full text. Responses are indented and be used to sort and filter their messages. Then, we suggest responses to responses are further indented. The responses new features that could be introduced, to make the ratings to any comment are listed in chronological order, with the more useful to more readers. Evidence about users’ oldest ones first. At the top level, the direct responses to an preferences comes both from responses to subjective survey initial news story, full text is shown for comments that have questions, and from objective measures of users’ choices of a score of 1 or higher. For comments deeper in the thread setting when reading comments. (i.e., replies to other comments), full text is shown for Literature on user access of customization features indicates comments rated 4 or higher, a single line is shown for that few people take advantage of advanced interface comments rated 1-4, and the comment is omitted if it’s options. Mackay [16] conducted interviews with and score is below the threshold of 1. collected automatic records of customization activities of At the time of data collection, any reader, anonymous or 51 members of a project at MIT over a four month period. registered, could make a local change to the display of She found that users engaged in a continual analysis of the comments for the current story, using the options shown at cost of learning to customize versus the benefit of having the top of Figure 1. Through pull-down menus shown at the done so. A significant barrier includes the lack of time to top of Figure 1, a reader can set the threshold to any value learn the specific tools available. Triggers for changing between -1 and +5. A reader can also sort messages based preferences included when changing allowed the user to on their ratings; at each level of the response hierarchy avoid learning new behaviors. Customizing to make an Figure 1: Options for changing comments settings temporarily within discussion forums.