3 Matching Annotations
- Dec 2019
- Aug 2018
Through spatio-temporalfiltering of messages we are able to observeevolution of topic signal that is consistent with rumor theory’s predictions. In the area immediately surrounding Moore wefind the strongest evidence that rumoring is an evolutionary process, as the topic and tone of messages shifts notably over thisthree-day span. Although these results may not necessarily generalize to all events, we dofind some initial support thatrumoring is a process marked by topical evolution over time. Once again, the spatio-temporalfiltering approach proves to berobust tool for measuring signal of hazard-related rumoring.
Using what is known about social responses to disaster events(impending or realized), we selectivelyfilter timestamped streams of geolocated, informal communication activity by timeand location in order to identify surges of rumoring activity in response to a disaster. Spatio-temporalfiltering enhances ourability to detect events by utilizing the signal produced by sources that are known (or expected) to produce reliable infor-mation, thereby enhancing our ability to detect distinct activity patterns above and beyond typical global signal (i.e. back-ground noise representing the array of signals irrelevant to our focus)
Filtering technique relies on timestamp and geolocation.
Per Sloan (2015), only 0.85% of tweets are geotagged (approx. 4M tweets per day)