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What is Academic Integrity? | Academic Integrity at MIT - 0 views

integrity.mit.edu 1.5 DGL Digital Literacy Vocabulary Academic Integrity
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    Academic Integrity MIT
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Doninger v. Niehoff, 514 F. Supp. 2d 199 - Dist. Court, D. Connecticut 2007 - Google Sc... - 0 views

scholar.google.com/scholar_case 1.5 DGL Digital Literacy Vocabulary Blogging
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    Frustrated at school officials over developments regarding a music festival she had been planning, Avery posted a public message to her fellow students on a social networking site. Just about everyone but Avery agrees that the manner in which Avery expressed her frustration was offensive and inappropriate. For the message used a vulgar, slang term to describe school officials, it contained at best misleading and at worse false information regarding the music festival, and it called on students and their parents to write the school superintendent in order to "piss her off more." When school officials - who had advised Avery before she made her blog posting about the proper way for student leaders to address issues of concern with the administration - discovered the message, they disqualified Avery from running for class secretary for her senior year. According to school officials, Avery's conduct in posting the blog message failed to display the qualities of civility and citizenship that the school expected of class officers and leaders.
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http://www.aaai.org/Papers/Symposia/Spring/2006/SS-06-03/SS06-03-020.pdf - 0 views

www.aaai.org/...SS06-03-020.pdf 1.5 DGL Digital Literacy Vocabulary Blogging
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    Watching specific information sources and summarizing the newly discovered opinions are important for governments to improve their services and for companies to improve their products (Dave et al., 2003 and Morinaga et al., 2002).
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http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.156.7392&rep=rep1&type=pdf#pag... - 0 views

citeseerx.ist.psu.edu/...download 1.5 DGL Digital Literacy Vocabulary Blogging
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      qilabs on 09 Feb 15
       
      Weblogs, or blogs as they are affectionately termed, are frequently updated websites, usually personal, with commentary and links. Link lists are as old as home pages, but a blog is far from a static link list or home page. A blog consists of many relatively short posts, usually time-stamped, and organised in reverse chronology so that a reader will always see the most recent post first. 
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Enabling Management Oversight in Corporate Blog Space.pdf - 0 views

diigo.com/07biv2 1.5 DGL Digital Literacy Vocabulary Blogging
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  • Analysis of a corpus of tens of thousands of blogs –incorporating close to 300 million words – indicates significant differences in writing style and content between male and female bloggers as well as among authors of different ages. Such differences can be exploited to determine an unknown author’s age and gender on the basis of a blog’s vocabulary.
  • Learning AlgorithmWe use the learning algorithm Multi-Class Real Winnow (MCRW) to learn models that classify blogs according to author gender and age, respectively. Since this algorithm is not well known, we describe it briefly
  • UTOMATED AUTHOR PROFILINGWhile we have found significant differences among bloggers of different ages and genders, the truest test of the significance of these differences is the extent to which they enable us to correctly predict an author’s age and gender
  • ...2 more annotations...
  • 40.0%50.0%60.0%70.0%80.0%90.0%100.0%genderagestyle contentallFigure 1 10-fold cross validation results for the age and gender classifiersClassed as 10's20's30's10's7036102717720's916632684430's17814651351Table 7 Confusion matrix for the age classifier using all featuresFor age, content proves to be slightly more useful than style, but – as in gender – the combination is most useful. The confusion matrix indicates that, using content and style features together, 10s are distinguishable from 30’s with accuracy above 96% and distinguishing 10s from 20s is also achievable with accuracy of 87.3%. Many 30s are mis-classed as 20s, however, yielding overall accuracy is 76.2%CONCLUSIONSWe have assembled a large corpus of blogs labeled for a variety of demographic attributes. This large sample permits us insight into the demographic distribution of bloggers. We have found that teenage bloggers are predominantly female, while older bloggers are predominantly male. Moreover, within each age group, male and female bloggers blog about different thing and use different blogging styles
  • We have assembled a large corpus of blogs labeled for a variety of demographic attributes. This large sample
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http://www.ra.ethz.ch/CDStore/www2008/airweb.cse.lehigh.edu/2005/proceedings.pdf#page=11 - 0 views

www.ra.ethz.ch/...proceedings.pdf 1.5 DGL Digital Literacy Vocabulary Blogging
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    We present an approach for detecting link spam common in blog comments by comparing the language models used in the blog post, the comment, and pages linked by the com- ments. In contrast to other link spam filtering approaches, our method requires no training, no hard-coded rule sets, and no knowledge of complete-web connectivity. Prelimi- nary experiments with identification of typical blog spam show promising results.
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http://ndn-newpol.civicactions.net/sites/ndn-newpol.civicactions.net/files/ViralVideoin... - 0 views

ndn-newpol.civicactions.net/...ViralVideoinPolitics.pdf 1.5 DGL Digital Literacy Vocabulary Viral Videos
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    VIRAL VIDEO IN POLITICS CASE STUDIES ON CREATING COMPELLING VIDEO
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