Twitter as an indicator for whereabouts of people? Correlating Twitter with UK census data

Steiger, Enrico; Westerholt, René; Resch, Bernd; Zipf, Alexander

doi:10.1016/j.compenvurbsys.2015.09.007

Cited by 143 publications

(100 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…There are several examples of comparisons of Twitter data against official census data in inhabited areas [5,7], and similar validation efforts can be made using visitor statistics [9,10]. In this paper, we aimed at comparing the spatio-temporal activity patterns presented in social media to surveyed activities in order to make a further validation effort on social media content from our study area.…”

Section: Discussionmentioning

confidence: 99%

“…These data have the potential to enrich existing data collection methods for mapping spatio-temporal activity patterns and location-based experiences of people. The potential of geotagged social media for mapping people's activities and movements has been mainly illustrated in urban environments [2][3][4][5][6][7]. There are also promising results for utilizing spatio-temporal information of social media posts for visitor monitoring in recreational revenues [10], landscape values [11], and travel patterns [34].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey

Heikinheimo

Minin

Tenkanen

et al. 2017

IJGI

226

101

View full text Add to dashboard Cite

Abstract:Protected area management and marketing require real-time information on visitors' behavior and preferences. Thus far, visitor information has been collected mostly with repeated visitor surveys. A wealth of content-rich geographic data is produced by users of different social media platforms. These data could potentially provide continuous information about people's activities and interactions with the environment at different spatial and temporal scales. In this paper, we compare social media data with traditional survey data in order to map people's activities and preferences using the most popular national park in Finland, Pallas-Yllästunturi National Park, as a case study. We compare systematically collected survey data and the content of geotagged social media data and analyze: (i) where do people go within the park; (ii) what are their activities; (iii) when do people visit the park and if there are temporal patterns in their activities; (iv) who the visitors are; (v) why people visit the national park; and (vi) what complementary information from social media can provide in addition to the results from traditional surveys. The comparison of survey and social media data demonstrated that geotagged social media content provides relevant information about visitors' use of the national park. As social media platforms are a dynamic source of data, they could complement and enrich traditional forms of visitor monitoring by providing more insight on emerging activities, temporal patterns of shared content, and mobility patterns of visitors. Potentially, geotagged social media data could also provide an overview of the spatio-temporal activity patterns in other areas where systematic visitor monitoring is not taking place.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey

Heikinheimo

Minin

Tenkanen

et al. 2017

IJGI

226

101

View full text Add to dashboard Cite

show abstract

“…Moreover, they are not evenly spread in space and among user groups, as youngsters tend to use social media more actively (Li, Goodchild, & Xu, 2013;Resch et al, 2017). These issues have been thoroughly discussed in existing literature (Steiger et al, 2015;Sui & Goodchild, 2011) and will be further detailed in the Discussion section. In addition, we want to point out that distinguishing personal and non-personal Twitter accounts was beyond the scope of this study.…”

Section: Datamentioning

confidence: 99%

“…This provides an opportunity to investigate what people actually think about parts of the city and the direct or indirect effects of a large event. Thus, several methods and analyses have been developed in the area of opinion mining (e.g., Pak & Paroubek, 2010) and semantic topic extraction (e.g., Steiger, Westerholt, Resch, & Zipf, 2015) for use in urban planning.…”

Section: Introductionmentioning

confidence: 99%

#London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data

Kovács-Györi

Ristea

Havas

et al. 2018

Self Cite

View full text Add to dashboard Cite

The dynamic nature of cities, understood as complex systems with a variety of concurring factors, poses significant challenges to urban analysis for supporting planning processes. This particularly applies to large urban events because their characteristics often contradict daily planning routines. Due to the availability of large amounts of data, social media offer the possibility for fine-scale spatial and temporal analysis in this context, especially regarding public emotions related to varied topics. Thus, this article proposes a combined approach for analyzing large sports events considering event days vs comparison days (before or after the event) and different user groups (residents vs visitors), as well as integrating sentiment analysis and topic extraction. Our results based on various analyses of tweets demonstrate that different spatial and temporal patterns can be identified, clearly distinguishing both residents and visitors, along with positive or negative sentiment. Furthermore, we could assign tweets to specific urban events or extract topics related to the transportation infrastructure. Although the results are potentially able to support urban planning processes of large events, the approach still shows some limitations including well-known biases in social media or shortcomings in identifying the user groups and in the topic modeling approach.

show abstract

“…Las TIC como enlace entre el mundo físico y el virtual Fuente: (Steiger et al, 2015) El Big Data y las TIC se antojan como nuevas fuentes al servicio de la ciudad. Con la Web 3.0 ha surgido el concepto de Spatial Big Data (SBD): grandes cantidades de información espacial que pueden ser capturadas, comunicadas, agregadas, almacenadas y analizadas (McKinsey & Company, 2011).…”

Section: Nuevas Fuentes De Datosunclassified

Visualizing the Data City

Ciuccarelli¹,

Lupi²,

Simeone

2014

SpringerBriefs in Applied Sciences and Technology

View full text Add to dashboard Cite

ResumenEl aumento de la demanda de movilidad en las ciudades ha conllevado una dinámica poco sostenible tanto a nivel social como ambiental. Para promover actuaciones hacía una movilidad sostenible es necesario el uso de fuentes de información dinámicas, con un alto detalle espacial y temporal (y de bajo coste) que permitan realizar diagnósticos eficientes de la situación de movilidad en nuestras ciudades. Las Tecnologías de Información y Comunicación y el Big Data aparecen como nuevas fuentes interactivas que responden a estas necesidades. En este artículo se realiza una revisión del estado del arte en el uso de estas nuevas fuentes de datos para el análisis de la movilidad urbana, contrastando su utilidad respecto a las fuentes tradicionales, clasificán-dolas, presentando las temáticas de investigación que ofrecen, y abordando los desafíos de cara al futuro.Palabras clave: movilidad, Smart Cities, TIC, redes sociales, Big Data. Abstract New sources and challenges for urban mobility studiesIncrement of mobility demand in cities has carried socially and environmentally an unsustainable dynamic. For a sustainable planning, dynamic, high spatial and temporal resolution, and low cost sources are needed. Information and Communication Technologies appear as new interactive sources able to meet these needs. In this article, a state of the art in these new data sources use for urban mobility analysis is implemented. These new technologies are contrasted with traditional sources, are classified, new investigation topics are presented, and future challenges are addressed.

show abstract

Twitter as an indicator for whereabouts of people? Correlating Twitter with UK census data

Cited by 143 publications

References 34 publications

User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey

User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey

#London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data

Visualizing the Data City

Contact Info

Product

Resources

About