short-paper

Emotion predictions in geo-textual data using spatial statistics and recommendation systems

Authors:

Andreas ZüfleAuthors Info & Claims

LocalRec '19: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising

Article No.: 5, Pages 1 - 4

https://doi.org/10.1145/3356994.3365508

Published: 05 November 2019 Publication History

Abstract

Microblogs are used by millions of users to express their emotions, such as joy, surprise and anger, on a plethora of different topics. For the same topic, different places may exhibit different emotions for identical topics. The goal of this work is to learn, model and predict emotions on various topics and in different cities. For this purpose, we propose a hybrid approach which combines spatial statistics (kriging) and recommendation system (matrix factorization-based). Our experimental evaluations, using millions of tweets across the United States, show that our hybrid approach outperforms individual approaches based on matrix factorization and Kriging alone. This case study shows the potential of combining spatial statistics methods such as Kriging with machine learning solutions to support knowledge discovery on spatial data.

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Cited By

Kravi EKanza YKimelfeld BReichart R(2021)Location Classification Based on TweetsProceedings of the 4th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery10.1145/3486635.3491075(51-60)Online publication date: 2-Nov-2021
https://dl.acm.org/doi/10.1145/3486635.3491075
Sikder AZüfle A(2020)Augmenting Geostatistics with Matrix Factorization: A Case Study for House Price EstimationISPRS International Journal of Geo-Information10.3390/ijgi90502889:5(288)Online publication date: 28-Apr-2020
https://doi.org/10.3390/ijgi9050288
Bouros PDasu TKanza YRenz MSacharidis D(2020)LocalRec 2019 workshop report: The Third ACM SIGSPATIAL Workshop on Location-Based Recommendations, Geosocial Networks and GeoadvertisingSIGSPATIAL Special10.1145/3383653.338366511:3(30-33)Online publication date: 13-Feb-2020
https://dl.acm.org/doi/10.1145/3383653.3383665

Index Terms

Emotion predictions in geo-textual data using spatial statistics and recommendation systems
1. Computing methodologies
  1. Machine learning
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

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Published In

cover image ACM Conferences

LocalRec '19: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising

November 2019

92 pages

ISBN:9781450369633

DOI:10.1145/3356994

Editors:
Panagiotis Bouros
Johannes Gutenberg University Mainz, Germany
,
Tamraparni Dasu
AT&T Labs - Research
,
Yaron Kanza
AT&T Labs - Research
,
Matthias Renz
Christian-Albrechts-Universität zu Kiel, Germany
,
Dimitris Sacharidis
Technische Universität Wien, Austria

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

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Published: 05 November 2019

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SIGSPATIAL

SIGSPATIAL '19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 5, 2019

Illinois, Chicago

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LocalRec '19 Paper Acceptance Rate 6 of 12 submissions, 50%;

Overall Acceptance Rate 17 of 26 submissions, 65%

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Cited By

Kravi EKanza YKimelfeld BReichart R(2021)Location Classification Based on TweetsProceedings of the 4th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery10.1145/3486635.3491075(51-60)Online publication date: 2-Nov-2021
https://dl.acm.org/doi/10.1145/3486635.3491075
Sikder AZüfle A(2020)Augmenting Geostatistics with Matrix Factorization: A Case Study for House Price EstimationISPRS International Journal of Geo-Information10.3390/ijgi90502889:5(288)Online publication date: 28-Apr-2020
https://doi.org/10.3390/ijgi9050288
Bouros PDasu TKanza YRenz MSacharidis D(2020)LocalRec 2019 workshop report: The Third ACM SIGSPATIAL Workshop on Location-Based Recommendations, Geosocial Networks and GeoadvertisingSIGSPATIAL Special10.1145/3383653.338366511:3(30-33)Online publication date: 13-Feb-2020
https://dl.acm.org/doi/10.1145/3383653.3383665

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