#TwitterSearch: a comparison of microblog search and web search
Proceedings of the fourth ACM international conference on Web search and data mining
Twitter under crisis: can we trust what we RT?
Proceedings of the First Workshop on Social Media Analytics
Joint inference for cross-document information extraction
Proceedings of the 20th ACM international conference on Information and knowledge management
On truth discovery in social sensing: a maximum likelihood estimation approach
Proceedings of the 11th international conference on Information Processing in Sensor Networks
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This demonstration illustrates an information aggregation and summarization service for social sensing applications. Social sensing, using mobile phones and other networked devices in the possession of individuals, has gained significant popularity in recent years. In some cases, the information collected is structured, such as numeric data from temperature sensors, accelerometers, or GPS devices. Aggregate statistical properties, such as expected values, standard deviations, and outliers, can be easily computed, and can be used to summarize the data set. In other cases, however, the collection includes unstructured data types such as text or images with textual annotations. The concepts of expected values and outliers are harder to define, yet it is still important to be able to aggregate and summarize the data. We demonstrate a system which can automatically summarize real-time textual data common to social sensing applications. Specifically, we focus on text messages that describe events in the environment. The output of our service provides a reliable summary of observations that can be used in many contexts from military intelligence to participatory sensing campaigns.