1,139 research outputs found
Social Media for Cities, Counties and Communities
Social media (i.e., Twitter, Facebook, Flickr, YouTube) and other tools and services with user- generated content have made a staggering amount of information (and misinformation) available. Some government officials seek to leverage these resources to improve services and communication with citizens, especially during crises and emergencies. Yet, the sheer volume of social data streams generates substantial noise that must be filtered. Potential exists to rapidly identify issues of concern for emergency management by detecting meaningful patterns or trends in the stream of messages and information flow. Similarly, monitoring these patterns and themes over time could provide officials with insights into the perceptions and mood of the community that cannot be collected through traditional methods (e.g., phone or mail surveys) due to their substantive costs, especially in light of reduced and shrinking budgets of governments at all levels. We conducted a pilot study in 2010 with government officials in Arlington, Virginia (and to a lesser extent representatives of groups from Alexandria and Fairfax, Virginia) with a view to contributing to a general understanding of the use of social media by government officials as well as community organizations, businesses and the public. We were especially interested in gaining greater insight into social media use in crisis situations (whether severe or fairly routine crises, such as traffic or weather disruptions)
TREC Incident Streams: Finding Actionable Information on Social Media
The Text Retrieval Conference (TREC) Incident Streams track is a new initiative that aims to mature social
media-based emergency response technology. This initiative advances the state of the art in this area through an
evaluation challenge, which attracts researchers and developers from across the globe. The 2018 edition of the track
provides a standardized evaluation methodology, an ontology of emergency-relevant social media information types,
proposes a scale for information criticality, and releases a dataset containing fifteen test events and approximately
20,000 labeled tweets. Analysis of this dataset reveals a significant amount of actionable information on social
media during emergencies (> 10%). While this data is valuable for emergency response efforts, analysis of the
39 state-of-the-art systems demonstrate a performance gap in identifying this data. We therefore find the current
state-of-the-art is insufficient for emergency responders’ requirements, particularly for rare actionable information
for which there is little prior training data available
TREC Incident Streams: Finding Actionable Information on Social Media
The Text Retrieval Conference (TREC) Incident Streams track is a new initiative that aims to mature social
media-based emergency response technology. This initiative advances the state of the art in this area through an
evaluation challenge, which attracts researchers and developers from across the globe. The 2018 edition of the track
provides a standardized evaluation methodology, an ontology of emergency-relevant social media information types,
proposes a scale for information criticality, and releases a dataset containing fifteen test events and approximately
20,000 labeled tweets. Analysis of this dataset reveals a significant amount of actionable information on social
media during emergencies (> 10%). While this data is valuable for emergency response efforts, analysis of the
39 state-of-the-art systems demonstrate a performance gap in identifying this data. We therefore find the current
state-of-the-art is insufficient for emergency responders’ requirements, particularly for rare actionable information
for which there is little prior training data available
Incident Streams 2019: Actionable Insights and How to Find Them
The ubiquity of mobile internet-enabled devices combined with wide-spread social media use during emergencies is posing new challenges for response personnel. In particular, service operators are now expected to monitor these online channels to extract actionable insights and answer questions from the public. A lack of adequate tools makes this monitoring impractical at the scale of many emergencies. The TREC Incident Streams (TREC-IS) track drives research into solving this technology gap by bringing together academia and industry to develop techniques for extracting actionable insights from social media streams during emergencies. This paper covers the second year of TREC-IS, hosted in 2019 with two editions, 2019-A and 2019-B, contributing 12 new events and approximately 20,000 new tweets across 25 information categories, with 15 research groups participating across the world. This paper provides an overview of these new editions, actionable insights from data labelling, and the automated techniques employed by participant systems that appear most effective
A Tutorial on Event Detection using Social Media Data Analysis: Applications, Challenges, and Open Problems
In recent years, social media has become one of the most popular platforms
for communication. These platforms allow users to report real-world incidents
that might swiftly and widely circulate throughout the whole social network. A
social event is a real-world incident that is documented on social media.
Social gatherings could contain vital documentation of crisis scenarios.
Monitoring and analyzing this rich content can produce information that is
extraordinarily valuable and help people and organizations learn how to take
action. In this paper, a survey on the potential benefits and applications of
event detection with social media data analysis will be presented. Moreover,
the critical challenges and the fundamental tradeoffs in event detection will
be methodically investigated by monitoring social media stream. Then,
fundamental open questions and possible research directions will be introduced
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