Event Detection in Social Media Sample Clauses

Event Detection in Social Media. ‌ Social media data, such as Twitter data, are an additional source of signals that are relevant for analysing financial risks in QualiMaster. Relevant events and their reflection in Social Media can have an impact on the financial situation either directly (e.g., disasters) or indiectly by influencing the reaction of actors in the financial market. Therefore we have implemented different detection algorithms for the detection of evolving events as well as bursts and other abnormalities within the incoming stream of social media data. The algorithms that deal with event detection form an algorithm family. An example ap- plication of this family can be seen in D6.3, where the Event Detection family is included as a component in the Focus Pipeline, a Storm pipeline for financial risk analysis recom- mending stocks to re-focus the attention of the user. Within this pipeline the Event De- tection component receives tweets from the preprocessing component and forwards any detected events to the keyword extraction component, where the events will be enriched with event describing keywords. Afterwards the Focus Recommendation component will aggregate events and forward them to the user pointing the user to marketplayers involved in the respective events as candidates to include into the list of his/her observed market players. Furthermore, the Event Detection family is closely related to the Event Prediction fam- ily, as introduced in D4.2, and work on both components is coordinated within the L3S team. However, Event Prediction uses the social media stream to predict events that might happen in the future, mainly focussing on events that are announced or expected (and therefore talked about in social media in combination with expected time points). In contrast, the Event Detection component solely focuses on current and evolving events that can be discovered by observing frequencies. Such events might have an impact on one or several stocks. Event detection algorithms can still be used for the last step of content-based event prediction (see D4.3, Section 3.2.2.2).
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