Database Reference
In-Depth Information
Fig. A.2
A view of the different components of TweetXplorer. The figure shows information
pertaining to three themes
analysis to aid its users in analyzing events via different perspectives in near real-
time.
TwitterMonitor
[
4
] is a system to detect emerging topics or trends in a Twitter
stream. The system identifies bursty keywords as an indicator of emerging trends,
and periodically groups them together to form emerging topics. Detected trends
can be visually analyzed through the system.
TEDAS
[
2
] is an event detection
and analysis system focused on crime and disaster events. TEDAS crawls event
related Tweets using a rule-based approach. Detected events are analyzed to extract
temporal and spatial information. The system also uses the location information
of the author's network to predict the location of a Tweet when the Tweet is not
geotagged.
SensePlace2
[
3
] supports collection and analysis of Tweets for keyword
searches on-demand. The system focuses on three primary views: text, map, and
timeline, to enable exploration of data and to acquire situational awareness.
A.3
External Libraries Used in This Topic
All the examples in this chapter are written primarily using Java and open source
libraries which can be downloaded at no cost to the reader. All the code samples
discussed in this topic can be obtained at the topic's companion website
http://
