Titlebook: Roles, Trust, and Reputation in Social Media Knowledge Markets; Theory and Methods Elisa Bertino,Sorin Adam Matei Book 2015 Springer Intern

instructive

From Invisible Algorithms to Interactive Affordances: Data After the Ideology of Machine Learningdemonstrate alternative approaches to information presentation. I do this in three domains: music, email and friending. I contend that these new approaches open up new ways of thinking about data while also providing significant new technological challenges.

Fulsome

嚙齒動(dòng)物

sacrum

Semantic and Social Spaces: Identifying Keyword Similarity with Relations people produce and share content, various content items are related to each other, and people have social relations such as collaboration and discussion. Identifying people’s expertise and topics is the first step in evaluating the quality of information in a network. Text semantic analysis and soc

Grievance

Emergent Social Roles in Wikipedia’s Breaking News Collaborationsmprovisation of order out of chaos,” equanimity of victims, emergence of serendipitous and egalitarian social ties, and redemptive moments of solidarity have characterized post-catastrophe communities for centuries, but are also intrinsically ephemeral and recede as the most acute phase passes. Foll

CRACY

G-spot

Predicting Low-Quality Wikipedia Articles Using User’s Judgements practical to model the quality of Wikipedia articles and to have inferior contents which bother readers or even mislead readers to be predicted. While identifying low-quality articles with manual efforts is a possible solution, it costs too much manpower and is too time-consuming. In this paper, we

恭維

From Invisible Algorithms to Interactive Affordances: Data After the Ideology of Machine Learningemploying personalization features). Instead of alphabetical or chronological order, information providers use the logic of machine learning to train the system. This ideology encourages less from users and more from data providers. I present examples, primarily from the notion of data-as-graphs to

REIGN

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