Search Results for author: Aaron Harwood

Found 9 papers, 1 papers with code

Where did you tweet from? Inferring the origin locations of tweets based on contextual information

no code implementations18 Nov 2022 Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read

We employ a tweet contexualizer (locBERT) which is one of the core components of the proposed model, to investigate multiple tweets' distributions for understanding Twitter users' tweeting behavior in terms of mentioning origin and non-origin locations.

Natural Language Understanding

Socially Enhanced Situation Awareness from Microblogs using Artificial Intelligence: A Survey

no code implementations13 Sep 2022 Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read

The rise of social media platforms provides an unbounded, infinitely rich source of aggregate knowledge of the world around us, both historic and real-time, from a human perspective.

Twitter conversations predict the daily confirmed COVID-19 cases

1 code implementation21 Jun 2022 Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read

Following the outbreak, the pandemic's seriousness has made people more active on social media, especially on the microblogging platforms such as Twitter and Weibo.

Time Series Analysis

Real-time Spatio-temporal Event Detection on Geotagged Social Media

no code implementations23 Jun 2021 Yasmeen George, Shanika Karunasekera, Aaron Harwood, Kwan Hui Lim

First, to address the challenge related to the unknown spatial resolution of events, a quad-tree method is exploited in order to split the geographical space into multiscale regions based on the density of social media data.

Event Detection

User Identification across Social Networking Sites using User Profiles and Posting Patterns

no code implementations22 Jun 2021 Prashant Solanki, Kwan Hui Lim, Aaron Harwood

With the prevalence of online social networking sites (OSNs) and mobile devices, people are increasingly reliant on a variety of OSNs for keeping in touch with family and friends, and using it as a source of information.

Geometry of Interest (GOI): Spatio-Temporal Destination Extraction and Partitioning in GPS Trajectory Data

no code implementations14 Mar 2016 Seyed Morteza Mousavi, Aaron Harwood, Shanika Karunasekera, Mojtaba Maghrebi

To improve the quality of the extracted SVLs, instead of using NNQ, we label the visited locations as the IDs of the POIs which geometrically intersect with the GPS observations.

Management

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