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Twitter is often used in quantitative studies that identify geographically-preferred topics, writing styles, and entities. These studies rely on either GPS coordinates attached to individual messages, or on the user-supplied location field…

计算与语言 · 计算机科学 2015-08-25 Umashanthi Pavalanathan , Jacob Eisenstein

Twitter is a useful resource to analyze peoples' opinions on various topics. Often these topics are correlated or associated with locations from where these Tweet posts are made. For example, restaurant owners may need to know where their…

机器学习 · 计算机科学 2021-06-28 Florina Dutt , Subhajit Das

In many Twitter studies, it is important to know where a tweet came from in order to use the tweet content to study regional user behavior. However, researchers using Twitter to understand user behavior often lack sufficient geo-tagged…

社会与信息网络 · 计算机科学 2017-11-21 Binxuan Huang , Kathleen M. Carley

We observe and report on a systematic relationship between population density and Twitter use. Number of tweets, number of users and population per unit area are related by power laws, with exponents greater than one, that are consistent…

社会与信息网络 · 计算机科学 2017-11-28 Rudy Arthur , Hywel Williams

Geo-tagged Twitter data has been used recently to infer insights on the human aspects of social media. Insights related to demographics, spatial distribution of cultural activities, space-time travel trajectories for humans as well as…

社会与信息网络 · 计算机科学 2019-07-30 Wei Lun Lim , Chiung Ching Ho , Choo-Yee Ting

Social media data provides propitious opportunities for public health research. However, studies suggest that disparities may exist in the representation of certain populations (e.g., people of lower socioeconomic status). To quantify and…

计算机与社会 · 计算机科学 2017-11-07 Nina Cesare , Christan Grant , Jared B. Hawkins , John S. Brownstein , Elaine O. Nsoesie

This paper introduces a spatiotemporal analysis framework for estimating hourly changing population distribution in urban areas using geo-tagged tweets (the messages containing users' physical locations), land use data, and dasymetric maps.…

物理与社会 · 物理学 2018-10-17 Ming-Hsiang Tsou , Hao Zhang , Atsushi Nara , Su Yeon Han

This paper evaluates large georeferenced corpora, taken from both web-crawled and social media sources, against ground-truth population and language-census datasets. The goal is to determine (i) which dataset best represents population…

计算与语言 · 计算机科学 2020-04-03 Jonathan Dunn , Ben Adams

Computational social science studies often contextualize content analysis within standard demographics. Since demographics are unavailable on many social media platforms (e.g. Twitter) numerous studies have inferred demographics…

计算与语言 · 计算机科学 2021-07-13 Zach Wood-Doughty , Paiheng Xu , Xiao Liu , Mark Dredze

Modern society habitually uses online social media services to publicly share observations, thoughts, opinions, and beliefs at any time and from any location. These geotagged social media posts may provide aggregate insights into people's…

社会与信息网络 · 计算机科学 2014-11-25 Derek Doran , Swapna Gokhale , Aldo Dagnino

Real-time tweets can provide useful information on evolving events and situations. Geotagged tweets are especially useful, as they indicate the location of origin and provide geographic context. However, only a small portion of tweets are…

社会与信息网络 · 计算机科学 2019-10-08 Luke S. Snyder , Morteza Karimzadeh , Ray Chen , David S. Ebert

This research is aimed to solve the tweet/user geolocation prediction task and provide a flexible methodology for the geotagging of textual big data. The suggested approach implements neural networks for natural language processing (NLP) to…

计算与语言 · 计算机科学 2025-01-13 Kateryna Lutsai , Christoph H. Lampert

Social media is considered a democratic space in which people connect and interact with each other regardless of their gender, race, or any other demographic aspect. Despite numerous efforts that explore demographic aspects in social media,…

社会与信息网络 · 计算机科学 2018-04-03 Johnnatan Messias

The emergence of large stores of transactional data generated by increasing use of digital devices presents a huge opportunity for policymakers to improve their knowledge of the local environment and thus make more informed and better…

计算机与社会 · 计算机科学 2017-10-27 Graham McNeill , Jonathan Bright , Scott A. Hale

Associating geo-coordinates with the content of social media posts can enhance many existing applications and services and enable a host of new ones. Unfortunately, a majority of social media posts are not tagged with geo-coordinates. Even…

信息检索 · 计算机科学 2014-10-20 Derek Doran , Swapna Gokhale , Aldo Dagnino

Accurate estimation of user location is important for many online services. Previous neural network based methods largely ignore the hierarchical structure among locations. In this paper, we propose a hierarchical location prediction neural…

社会与信息网络 · 计算机科学 2019-10-30 Binxuan Huang , Kathleen M. Carley

Demographics, in particular, gender, age, and race, are a key predictor of human behavior. Despite the significant effect that demographics plays, most scientific studies using online social media do not consider this factor, mainly due to…

社会与信息网络 · 计算机科学 2016-03-08 Jisun An , Ingmar Weber

The geolocation of online information is an essential component in any geospatial application. While most of the previous work on geolocation has focused on Twitter, in this paper we quantify and compare the performance of text-based…

计算与语言 · 计算机科学 2018-11-20 Konstantinos Pappas , Mahmoud Azab , Rada Mihalcea

Nowadays, geographic information related to Twitter is crucially important for fine-grained applications. However, the amount of geographic information avail- able on Twitter is low, which makes the pursuit of many applications challenging.…

计算与语言 · 计算机科学 2017-05-09 Hayate Iso , Shoko Wakamiya , Eiji Aramaki

We propose an end-to-end neural network to predict the geolocation of a tweet. The network takes as input a number of raw Twitter metadata such as the tweet message and associated user account information. Our model is language independent,…

计算与语言 · 计算机科学 2017-10-16 Jey Han Lau , Lianhua Chi , Khoi-Nguyen Tran , Trevor Cohn
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