Online news is a crowded field, and personalized news is becoming the Holy Grail for news publishers facing decreased revenues and outdated business models. The challenge in personalizing the news is matching what people want with what they get. Kiffets delivers information via curated Channels that 1) collect articles from sources such as RSS feeds 2) organize the articles automatically by topic in each Channel and 3) include not only mainstream news but editorial commentary, blogs, etc. Kiffets then serves up your personalized information diet in terms of the Channels that you subscribe to.
Many online journalists, bloggers, and social news sites already serve as curators by collecting links and adding commentary. However, we at Kiffets believe that a new form of curation is needed that helps curators work more efficiently. Kiffets, like many social media systems, draws on three sources of power:
- Light work of the many. Properly harnessed, the light or casual “work” of many users can yield the “wisdom of the crowd”. This refers to the casual “work” of the many users of a social media system. The work may be incidental to using the system — such as determining popularity of articles and indexes by measuring how people use them. There may also be direct but lightweight actions, such as users commenting or voting on articles.
- Hard work of the few. Typically, the “few” contribute expertise that benefits others. In Wikipedia, this is the work of the people who write and edit articles. In a social index, this is the work of the curators of indexes.
- Tireless work of the machines. This is the automatic information processing work of computers in support of the users, including web crawling, article collection, and machine learning.
Kiffets shares a similar distribution of user roles as other social media. Most users are just consumers of information who provide simple feedback to the system. A smaller percentage of users creates single-topic Channels, which are the easiest to create. However, a small but growing number of users have graduated to more advanced curator roles, creating multiple-topic Channels and sharing them with friends. Since we expect this style of viral sharing to drive adoption of social indexing, Kiffets introduces several features to reduce the effort needed by curators in creating and sharing indexes. These facilities shift some of the required effort from the “hard work of the few” to the other two sources of power.
- Evergreen collection. Articles are collected regularly from designated web sources and automatically classified into the topics for the Channels. In contrast with social news sites such as Reddit, this reduces the burden of curators or other users in finding and submitting articles.
- Topic training. Curators define a tree of topics and provide articles as positive (on-topic) and negative (off-topic) examples. Given these examples, machine learning algorithms create computational models that automatically classify articles by topic. In contrast with tagging sites such as Delicious, this reduces the burden of identifying categories for articles and provides consistent categorization.
- Inline maintenance. Curators can mark articles as off-topic (on article reading pages) or submit new articles to their sources (using a Kiff It! book marklet) while browsing the web.