Difference between revisions of "Is it Really About Me? Message Content in Social Awareness Streams"
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This [[Category::paper]] uses quantitative (statistical) methods to analyze the Twitter use postings in a qualitative manner. The authors used human coders to categorize the Twitter user feeds into 9 categories, and answered the research questions such as: what are the most common message types of Twitter user? What these type of messages say about the user him/herself? How are these differences in users' content practices related to other user characteristics? | This [[Category::paper]] uses quantitative (statistical) methods to analyze the Twitter use postings in a qualitative manner. The authors used human coders to categorize the Twitter user feeds into 9 categories, and answered the research questions such as: what are the most common message types of Twitter user? What these type of messages say about the user him/herself? How are these differences in users' content practices related to other user characteristics? | ||
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+ | == Method used == | ||
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+ | Each tweet is examined by exactly two human coder. The coder can assign multiple categories to a tweet, and the union of the categories from each coder is considered as the final category for the tweet. |
Revision as of 22:30, 5 November 2012
Contents
Citation
Mor Naaman, Jeffrey Boase, and Chih-Hui Lai. Is it Really About Me? Message Content in Social Awareness Streams.
Online version
Summary
This paper uses quantitative (statistical) methods to analyze the Twitter use postings in a qualitative manner. The authors used human coders to categorize the Twitter user feeds into 9 categories, and answered the research questions such as: what are the most common message types of Twitter user? What these type of messages say about the user him/herself? How are these differences in users' content practices related to other user characteristics?
Method used
Each tweet is examined by exactly two human coder. The coder can assign multiple categories to a tweet, and the union of the categories from each coder is considered as the final category for the tweet.