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FutureStarrAA Earthquake Los Angeles Twitter
New York was just struck by a series of powerful earthquakes, with the epicenter being a building site in Lower Manhattan. Tremors of magnitude 4. 3 and 4. 5 were felt in Queens and Brooklyn. This morning, a magnitude 4. 1 earthquake was felt in downtown Los Angeles and was apparently due to the power of the social media of the time.
Time accelerating Benioff strain releasebefore the mainshock has been observed inall five cases of strong (M > 6.0) shallowmainshocks, which have occurred during thelast four decades in the area surroundingthe Adriatic Sea. This observation supportsthe idea that strong mainshocks arepreceded by accelerating seismic crustaldeformation due to the generation ofintermediate magnitude shocks (preshocks).It is further shown that the values ofparameters calculated from these datafollow appropriately modified relations,which have previously been proposed asadditional constraints to the criticalearthquake model and to the correspondingmethod of intermediate term earthquakeprediction. Thus, these results show thatthe identification of regions wheretime-accelerating Benioff strain followssuch constraints may lead to usefulinformation concerning the epicenter,magnitude and origin time of oncomingstrong mainshocks in this area. Theprocedure for identification of thetime-acceleration is validated byappropriate application on synthetic butrealistic random catalogues. Largerdimension of critical regions in Adriaticcompared to such regions in the Aegean isattributed to an order of magnitude smallerseismic deformation of the crust in theformer in comparison to the latter.
We describe an approach for extracting semantics of tags, unstructured text-labels assigned to resources on the Web, based on each tag's usage patterns. In particular, we fo- cus on the problem of extracting place and event seman- tics for tags that are assigned to photos on Flickr, a popu- lar photo sharing website that supports time and location (latitude/longitude) metadata. We analyze two methods inspired by well-known burst-analysis techniques and one novel method: Scale-structure Identification. We evaluate the methods on a subset of Flickr data, and show that our Scale-structure Identification method outperforms the exist- ing techniques. The approach and methods described in this work can be used in other domains such as geo-annotated web pages, where text terms can be extracted and associated with usage patterns. Categories and Subject Descriptors: H.1.m (MODELS AND PRINCIPLES): Miscellaneous .
The publicly available data, such as the massive and dynamically updated news and social media data streams (a.k.a. big data), cover a wide range of social activities, personal views, and expressions. Effective research and application rely heavily on the ability of comprehending and discovering the knowledgepatterns underlying this big data, from which the notion of an event serves as a cornerstone in building up more complex knowledge structures. Establishing methodologies and techniques for discovering real-world events from such large amounts of data, as well as for managing and analyzing such events in an efficient and aesthetic manner, is crucial and challenging. In this paper, we present an event cube framework devised to support various collection, consolidation, fusion, and analysis tasks for suicidal events. More specifically, we present a mechanism for data collection over multiple data sources in both passive and active manners, and promote the mappings constructed from various representation spaces for data consolidation. Furthermore, multimodal fusion is devised to integrate multiple data intrinsic structures and learn discriminative data representations so as to process heterogeneous multimodal data efficiently. Finally, the event cube model is developed to support event organization and contextualization with hierarchical and analytical operations. A case study is provided to demonstrate the capabilities and benefits of our event cube facilities supporting on-line analytical processing of suicidal events and their relationships.
Enterprise software should seriously consider this social computing phenomenon and leverage its capabilities by integrating such a tool in their offerings. For instance a social CRM application can use such a tool to help sales people effectively follow, collaborate, and close opportunities. The customer support system can provide transparency into the defect resolution process by service representatives tweeting the progress instead of logging it in semi-static IT ticket systems.