4.6 Article

Predicting Location of Tweets Using Machine Learning Approaches

Related references

Note: Only part of the references are listed.
Article Engineering, Multidisciplinary

Pre-HLSA: Predicting home location for Twitter users based on sentimental analysis

Aml Mostafa et al.

Summary: This paper introduces a new model, Pre-HLSA, for predicting the home locations of Twitter users based on sentiment analysis. The model analyzes tweet features to predict user locations, achieving promising performance compared to previous methods and providing geospatial services in areas such as epidemic dispersion.

AIN SHAMS ENGINEERING JOURNAL (2022)

Article Computer Science, Information Systems

Predicting Geolocation of Tweets: Using Combination of CNN and BiLSTM

Rhea Mahajan et al.

Summary: This study successfully predicted the geolocation of real-time tweets at the city level using a combination of convolutional neural network and a bidirectional long short-term memory. The accuracy achieved was 92.6%, with a median error of 22.4 km, showing significant improvement over baseline methods.

DATA SCIENCE AND ENGINEERING (2021)

Article Computer Science, Information Systems

Real-time event detection from the Twitter data stream using the TwitterNews plus Framework

Mahmud Hasan et al.

INFORMATION PROCESSING & MANAGEMENT (2019)

Article Computer Science, Hardware & Architecture

Twitter Analysis for Intelligent Transportation

Sarah Alhumoud

COMPUTER JOURNAL (2019)

Article Computer Science, Artificial Intelligence

A Survey of Location Prediction on Twitter

Xin Zheng et al.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2018)

Article Statistics & Probability

A random forest guided tour

Gerard Biau et al.

Article Statistics & Probability

A random forest guided tour

Gerard Biau et al.

Article Computer Science, Theory & Methods

Processing Social Media Messages in Mass Emergency: A Survey

Muhammad Imran et al.

ACM COMPUTING SURVEYS (2015)

Proceedings Paper Computer Science, Artificial Intelligence

Fine-Grained Geolocalisation of Non-Geotagged Tweets

Pavlos Paraskevopoulos et al.

PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015) (2015)

Proceedings Paper Computer Science, Artificial Intelligence

On the Accuracy of Hyper-local Geotagging of Social Media Content

David Flatow et al.

WSDM'15: PROCEEDINGS OF THE EIGHTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING (2015)

Article Computer Science, Artificial Intelligence

Home Location Identification of Twitter Users

Jalal Mahmud et al.

ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY (2014)

Article Geography

Where in the World Are You? Geolocation and Language Identification in Twitter

Mark Graham et al.

PROFESSIONAL GEOGRAPHER (2014)

Proceedings Paper Computer Science, Interdisciplinary Applications

Estimating the Locations of Emergency Events from Twitter Streams

Ji Ao et al.

2ND INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT, ITQM 2014 (2014)

Article Computer Science, Artificial Intelligence

Named Entity Recognition for Tweets

Xiaohua Liu et al.

ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY (2013)

Article Computer Science, Information Systems

EvenTweet: Online Localized Event Detection from Twitter

Flamed Abdelhaq et al.

PROCEEDINGS OF THE VLDB ENDOWMENT (2013)

Article Biotechnology & Applied Microbiology

What is a support vector machine?

William S. Noble

NATURE BIOTECHNOLOGY (2006)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)