A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Filters
Weakly Supervised Classification of Tweets for Disaster Management
2017
European Conference on Information Retrieval
Preserved Fulltext
Given this important role, real-time analysis of social media contents to locate, organize and use valuable information for disaster management is crucial. ...
In this paper, we propose self-learning algorithms that, with minimal supervision, construct a simple bag-of-words model of information expressed in the news about various natural disasters. ...
We use this topic-based classification scheme as a baseline because, it is also weakly supervised, like our approach. ...
dblp:conf/ecir/PalshikarAP17
fatcat:vryisecpajgq3a3bz6hrbwlwse
Weakly-Supervised Fine-Grained Event Recognition on Social Media Texts for Disaster Management
2020
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
People increasingly use social media to report emergencies, seek help or share information during disasters, which makes social networks an important tool for disaster management. ...
The evaluation on two hurricanes, Harvey and Florence, shows that using only 1-2 person-hours of human supervision, the rapidly trained weakly supervised classifiers outperform supervised classifiers trained ...
Supplemental Material Here is the full list of keywords used for each event category (Section Event Categories and Event Keywords). ...
doi:10.1609/aaai.v34i01.5391
fatcat:thnrvelrffav3n653xr2i5dbfi
Microblogging during the European Floods 2013
2015
International Journal of Information Systems for Crisis Response and Management
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
To ease the analysis of data we suggest a retweet ratio, which is illustrated to be higher with important tweets and may help selecting tweets for mining. ...
Social media is becoming more and more important in crisis management. ...
ACKNOWLEDGEMENTS The research project EmerGent' was funded by a grant of the European Union (FP7 No. 608352). ...
doi:10.4018/ijiscram.2015010102
fatcat:jrw6sdcj2rh7ni5fzwcpwjav5q
Classification of colloquial Arabic tweets in real-time to detect high-risk floods
2017
2017 International Conference On Social Media, Wearable And Web Analytics (Social Media)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Another technique combined three classifiers by computing the model scores of a weakly supervised, strongly supervised, and semi-supervised classifiers. ...
Data labelling stage The supervised learning of classification algorithms requires manual data labelling. ...
doi:10.1109/socialmedia.2017.8057358
fatcat:p35p3jcxzberhhikay6mtj7shq
An Ontology-Based Approach to Social Media Mining for Crisis Management
2014
Extended Semantic Web Conference
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
We illustrate a number of strategies for customizing the system to process social media texts such as Twitter messages, which are currently seen as a crucial source of information for crisis management ...
We describe an existing multilingual information extraction system that automatically detects event information on disasters, conflicts and health threats in near-real time from a continuous flow of on-line ...
In [1] we report about an evaluation on populating a microontology for disaster management with instances of events extracted from a stream of tweets published during several big tropical storms, in ...
dblp:conf/esws/ZavarellaTSG14
fatcat:ofystmh5dzbvhjwloefhlra3l4
A comparative review of the challenges encountered in sentiment analysis of Indian regional language tweets vs English language tweets
2018
International Journal of Engineering & Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Sentiment analysis of tweets is a challenging task. ...
This paper makes a critical review on the comparison of the challenges associated with sentiment analysis of Tweets in English Language versus Indian Regional Languages. ...
It can be useful in facilitating the requirements of those influenced by disaster. The tweets in the actual form involve several slang words and grammatical errors because of tweets informal nature. ...
doi:10.14419/ijet.v7i2.21.12394
fatcat:b6ey3aciwnerpopcijvs6wunrq
Multimodal Categorization of Crisis Events in Social Media
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Recent developments in image classification and natural language processing, coupled with the rapid growth in social media usage, have enabled fundamental advances in detecting breaking events around the ...
By processing billions of texts and images a minute, events can be automatically detected to enable emergency response workers to better assess rapidly evolving situations and deploy resources accordingly ...
and next-sentence prediction tasks as weakly-supervised pre-training. ...
doi:10.1109/cvpr42600.2020.01469
dblp:conf/cvpr/AbavisaniWHTJ20
fatcat:ioj4qpl7ynd2rmehadhaqfkdwq
CROWD4EMS: A CROWDSOURCING PLATFORM FOR GATHERING AND GEOLOCATING SOCIAL MEDIA CONTENT IN DISASTER RESPONSE
2019
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Community-driven initiatives such as Stand By Task Force (SBTF) or GISCorps have shown great potential by crowdsourcing the acquisition, analysis, and geolocation of social media data for disaster responders ...
This paper illustrates the use of a crowdsourcing platform that combines automatic methods for gathering information from social media and crowdsourcing techniques, in order to manage and aggregate volunteers ...
Out of the 236 classified tweets, the volunteers fully agreed on 146 classifications (61.35%), reached a high agreement on 57 classifications (23.95%), and did not reach an agreement in 33 classifications ...
doi:10.5194/isprs-archives-xlii-3-w8-331-2019
fatcat:5jvgxzzpprdu5mtfjot73ol5ry
Twitter sentiment classification for measuring public health concerns
2015
Social Network Analysis and Mining
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We are measuring public concern using a two-step sentiment classification approach. In the first step, we distinguish Personal tweets from News (i.e., Non-Personal) tweets. ...
Based on the number of tweets classified as Personal Negative, we compute a Measure of Concern (MOC) and a timeline of the MOC. ...
Acknowledgments This work was partially funded by a CUNY PSC research grant and partially sponsored by Intelligent Automation Inc. for the summer internship training for X. Ji. ...
doi:10.1007/s13278-015-0253-5
pmid:32226558
pmcid:PMC7096866
fatcat:4uafp234k5bsnbtfeywv5vr42i
Random Forest Location Prediction from Social Networks during Disaster Events
2019
2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Rapid location and classification of data posted on social networks during time-critical situations such as natural disasters, crowd movement and terrorism is very useful way to gain situational awareness ...
Identification of Tweets and their precise location are still inaccurate. ...
This is accomplished through the use of bagging and a classification and regression tree (CART) learning algorithm in order to build a large collection of "de-correlated" decision trees. ...
doi:10.1109/snams.2019.8931863
dblp:conf/snams/OuaretBSAB19
fatcat:ykkribqobrguvojqb2dtta72py
Knowledge-Based Tweet Classification for Disease Sentiment Monitoring
[chapter]
2016
Studies in Computational Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Ji et al. weakly correlated with the peaks of the News timeline without any appreciable time delay or lead. ...
Disease monitoring and tracking is of tremendous value, not only for containing the spread of contagious diseases but also for avoiding unnecessary public concerns and even panic. ...
supervised training data. ...
doi:10.1007/978-3-319-30319-2_17
fatcat:zcbjsn6xpneqvac64lrnhejtf4
Location reference recognition from texts: A survey and comparison
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
To fill these research gaps, this review first summarizes seven typical application domains of geoparsing: geographic information retrieval, disaster management, disease surveillance, traffic management ...
, spatial humanities, tourism management, and crime management. ...
For example, for traffic management and disaster management that rely on informal texts and require fine-grained locations, GazPNE2 is a good option; for crime management and tourism management that rely ...
arXiv:2207.01683v1
fatcat:xiy7az4veza6lm52c6yj7mnoe4
Emotion Recognition by Textual Tweets Classification Using Voting Classifier(LR-SGD)
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Seven Machine Learning models are implemented for emotion recognition by classifying tweets as happy or unhappy. ...
Sentiment analysis is a technique used to analyze the attitude, emotions and opinions of different people towards anything, and it can be carried out on tweets to analyze public opinion on news, policies ...
PROPOSED MODELS FOR TWEETS SENTIMENT CLASSIFICATION In this section classifiers utilized for tweet classification will be discussed. ...
doi:10.1109/access.2020.3047831
fatcat:ayncrponabffdopv7oaoofufkm
Assessment on the Use of Meteorological and Social Media Information for Forest Fire Detection and Prediction in Riau, Indonesia
2021
Sustainability
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The policy implications of these results suggest that crowdsourced data can be included in the fire management system in Indonesia to support early fire detection and fire disaster mitigation efforts. ...
The existing approaches that BMKG and other Indonesian agencies use to detect fire activity are reviewed and a novel approach for early fire detection is proposed based on the crowdsourcing of tweets. ...
The authors acknowledge the help of Maria Flatau with discussion of large-scale indices. Michał Łabuz processed the TAGGS algorithm and ...
doi:10.3390/su132011188
fatcat:sg3a3ayssjbozbjch4nmzzt43i
Localizing and Quantifying Damage in Social Media Images
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
., tweets) or images posted by eyewitnesses of a disaster. Most of the existing research explores the use of text in identifying situational awareness information useful for disaster response teams. ...
Our proposed approach enables the use of social network images for post-disaster damage assessment and provides an inexpensive and feasible alternative to the more expensive GIS approach. ...
Many studies have shown the utility of social media information for disaster management and response teams. ...
arXiv:1806.07378v1
fatcat:ylojycv4j5fgjjokisjrrrwi6e
« Previous
Showing results 1 — 15 out of 163 results