2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) 2014
DOI: 10.1109/asonam.2014.6921633
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Accelerate the detection of trends by using sentiment analysis within the blogosphere

Abstract: Information about upcoming trends is considered to be a valuable source of knowledge for both, companies and individuals. A large number of market analysts working at monitoring a particular business field, with many employing manual methods to do so. Since the amount of available data on the internet is far too high for humans to monitor, which carries a major risk of substantial amount of information being missed, the necessity arose to detect emerging trends automatically. Weblogs are an important medium to… Show more

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Cited by 3 publications
(2 citation statements)
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“…It is shown that influencers hold their status among different topics. Hennig et al [4] use information retrieval approaches to identify trends inside unstructured blog data. They state that tags as part of blog meta information and links influence whether some topic causes a trend.…”
Section: Related Workmentioning
confidence: 99%
“…It is shown that influencers hold their status among different topics. Hennig et al [4] use information retrieval approaches to identify trends inside unstructured blog data. They state that tags as part of blog meta information and links influence whether some topic causes a trend.…”
Section: Related Workmentioning
confidence: 99%
“…Roshanaei e Mishra (2015) mention that current experience and feeling of the users can be found in emoticons and mood updated by users. Hennig et al (2014) provide an overview about the emerging trend of topics; closest to this work is Saito, Tomioka e Yamanishi (2014) who are studying early detection of persistent topics. On the other hand, 120,000 fraudulent accounts were investigated by Thomas et al (2013).…”
Section: Individual Data Found On Social Networkmentioning
confidence: 99%