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Title:
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TREND CLASSIFICATION METHODOLOGY |
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Author(s):
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Radek Malinský, Ivan Jelínek |
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ISBN:
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978-989-8533-16-6 |
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Editors:
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Bebo White and Pedro Isaías |
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Year:
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2013 |
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Edition:
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Single |
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Keywords:
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Sentiment Analysis, Trend Classification, Web 2.0, Webometrics |
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Type:
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Doctoral Paper |
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First Page:
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389 |
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Last Page:
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393 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Web 2.0 (social networking, blogging, online forums, etc.) has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. It is necessary to design suitable metric for such volume of information, which would reflect semantic content of pages in the better way. One of the options for more accurate comprehension of semantic information is to use a sophisticated analysis of sentences called Sentiment Analysis. This paper discusses a novel model for gathering and processing data from Web 2.0. The model builds on webometrics and starts from the idea that almost any text can be machine-recognized. This idea is further verified using proposed methodology for a trend assessment. |
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