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Enabling Semantic User Context to Enhance Twitter Location Prediction · Study

WorkEnabling Semantic User Context to Enhance Twitter Location Prediction

Abeer ElKorany2016

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Workhybrid2016

Enabling Semantic User Context to Enhance Twitter Location Prediction

6 citations·0/0 files stored·International Conference on Agents and Artificial Intelligence (ICAART)

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Human Mobility and Location-Based Analysis Privacy-Preserving Technologies in Data Data Management and Algorithms

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References

2011Friendship and mobility 2010You are where you tweet 2011Tweets from Justin Bieber's heart 2013What's Your Next Move: User Activity Prediction in Location-based Social Networks 2014Home Location Identification of Twitter Users 2009Analysis of a Location-Based Social Network 2012Object matching in tweets with spatial models

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2020Predicting the Tweet Location Based on KNN-Sentimental Analysis

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Papers that cite the same references — the relational fallback while embeddings are still backfilling.

2019Twitter user geolocation using web country noun searchesarticle · 4 shared references 2015Mining Human Mobility in Location-Based Social Networksarticle · 4 shared references 2014Accurate Local Estimation of Geo-Coordinates for Social Media Postspreprint · 4 shared references 2018Mining location from social media: A systematic reviewreview · 3 shared references 2013Data Analysis on Location-Based Social Networkschapter · 3 shared references 2017The Effect of Population and "Structural" Biases on Social Media-based Algorithmsother · 3 shared references

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Year2016

Typeother

Published2016-01-01

VenueInternational Conference on Agents and Artificial Intelligence (ICAART)

Languageen

Citations6

Files0 public / 0

ShelfHuman Mobility and Location-Based Analysis

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doi10.5220/0005749502230230

openalex_workW2344630641

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