Building Web Reputation Systems- P5

Building Web Reputation Systems- P5:Today’s Web is the product of over a billion hands and minds. Around the clock andaround the globe, people are pumping out contributions small and large: full-lengthfeatures on Vimeo, video shorts on YouTube, comments on Blogger, discussions onYahoo! Groups, and tagged-and-titled Del.icio.us bookmarks. User-generated contentand robust crowd participation have become the hallmarks of Web 2.0.
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Building Web Reputation Systems- P5Users’ comments are usually freeform (unstructured) textual data. They typically arecharacter-constrained in some way, but the constraints vary depending on the context:the character allowance for a message board posting is generally much greater thanTwitter’s famous 140-character limit.In comment fields, you can choose whether to accommodate rich-text entry and dis-play, and you can apply certain content filters to comments up front (for instance, youcan choose to prohibit profanity or disallow fully formed URLs).Comments are often just one component of a larger compound reputation statement.Movie reviews, for instance, typically are a combination of 5-star qualitative claims(and perhaps different ones for particular aspects of the film) and one or more freeformcomment-type claims.Comments are powerful reputation claims when interpreted by humans, but they maynot be easy for automated systems to evaluate. The best way to evaluate text commentsvaries depending on the context. If a comment is just one component of a user review,the comment can contribute to a “completeness” score for that review: reviews withcomments are deemed more complete than those without (and, in fact, the commentfield may be required for the review to be accepted at all).If the comments in your system are directed at another contributor’s content (for ex-ample, user comments about a photo album or message board replies to a thread),consider evaluating comments as a measure of interest or activity around that reputableentity.Here are examples of claims in the form of text comments: • Flickr’s Interestingness algorithm likely accounts for the rate of commenting ac- tivity targeted at evaluating the quality of photos. • On Yahoo! Local, it’s possible to give an establishment a full review (with star ratings, freeform comments, and bar ratings for subfacets of a user’s experience with the establishment). Or a user can simply leave a rating of 1 to 5 stars. (This option encourages quick engagement with the site.) It’s easy to see that there’s greater business value (and utility to the community) in full reviews with well- written text comments, provided Yahoo! Local tracks the value of the reviews internally. Extending the Grammar: Building Blocks | 41 In our research at Yahoo!, we often probed notions of authenticity to look at how readers interpret the veracity of a claim or evaluate the authority or competence of a claimant. We wanted to know: when people read reviews online (or blog entries, or tweets), what are the specific cues that make them more likely to accept what they’re reading as accurate? Is there something about the presentation of material that makes it more trustworthy? Or is it the way the content author is presented? (Does an “expert” badge convince anyone?) Time and again, we found that it’s the content itself—the review, entry, or comment being evaluated—that makes up readers’ minds. If an ar- gument is well stated, if it seems reasonable, and if readers can agree with some aspect of it, then they are more likely to trust the content— no matter what meta-embellishment or framing it’s given. Conversely, research shows that users don’t see poorly written reviews with typos or shoddy logic as coming from legitimate or trustworthy sources. People really do pay attention to content.Media uploads. Reputation value can be derived from other types of qualitative claimtypes besides just freeform textual data. Any time a user uploads media—either inresponse to another piece of content (see Figure 3-1) or as a subcomponent of theprimary contribution itself—that activity is worth noting as a claim type.We distinguish textual claims from other media for two reasons: • While text comments typically are entered in context (users type them right into the browser as they interact with your site), media uploads usually require a slightly deeper level of commitment and planning on the user’s part. For example, a user might need to use an external device of some kind and edit the media in some way before uploading it. • Therefore, you may want to weight these types of contributions differently from text comments (or not, depending on the context) reflecting increased contribution value.A media upload consists of qualitative claim types that are not textual in nature: • Video • Images • Audio • Links • Collections of any of the aboveWhen a media object is uploaded in response to another content submission, considerit as input indicating ...