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otm:the_matching_of_causal_sequences [2011/06/27 06:00] aspectscript |
otm:the_matching_of_causal_sequences [2011/06/27 06:11] aspectscript |
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and Paul. Toti follows Dacha and Dacha follows Paul; Kuky follows nobody and nobody follows Kuky. The figure shows that Paul publishes a tweet and Dacha receives this tweet and retweets it. The figure also shows that Kuky publishes a tweet and nobody receives it. Based on the popularity measurement, | and Paul. Toti follows Dacha and Dacha follows Paul; Kuky follows nobody and nobody follows Kuky. The figure shows that Paul publishes a tweet and Dacha receives this tweet and retweets it. The figure also shows that Kuky publishes a tweet and nobody receives it. Based on the popularity measurement, | ||
and Paul would have published the same tweet, the popularity of Kuky's tweet is 0 because his tweet did not cause any retweet. An analysis based on the distributed causal relations observed between tweets and retweets can determine how many users retweet a given tweet. For example, Paul's tweet caused Dacha' | and Paul would have published the same tweet, the popularity of Kuky's tweet is 0 because his tweet did not cause any retweet. An analysis based on the distributed causal relations observed between tweets and retweets can determine how many users retweet a given tweet. For example, Paul's tweet caused Dacha' | ||
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- | As OTM supports the definition of entities that observe and react to a Web application execution trace, we have extended our prototype | + | Using WeCa, we show how to react to distributed |
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- | Social Web applications like [[http:// | + | |
- | * [[otm/ | + | * [[otm/ |
- | Go [[|OTM home]]. | + | Go [[../weca|WeCa home]]. |