Exploring geolocation issues in social media analytics A case study with Tweet messages

Social media data, such as Tweet messages, are sometimes associated with their geolocation. This information can be exploited to perform spatial analyses, resulting in geosocial analytics. However, the geolocation does not often correspond to the actual position of the author, but could be fictiously associated to the messages. The issues coming from the absence of Tweet geolocation metadata are explored in this paper, through a test case over Italy

Reading the social preferences of tourist destinations through social media data

The social preferences of individuals have been traditionally identified through traditional means using field techniques such as direct interviewing, observation and people-counting. The virtual layer of the social system currently allows new ways to identify the most preferred urban areas or venues. With that in mind, this paper aims to study how data from two Location-Based Social Networks: Foursquare and Twitter can shed light on empirical and theoretical observations about the spatial patterns characterizing where people tend to be and socialise in a tourist city. The methodology proposed consists of three stages. First, a self-developed desktop application retrieves geospatial data from the selected social networks. Then, the dataset obtained is organised and sorted. Finally, the georeferenced data is visualised and analysed and the trends are noted and discussed. To that end, the city of Benidorm was selected as a case study and the data was collected during the off-peak tourist season. The results demonstrate a correlation between the empirical assumptions and the findings from the social networks analysis about people’s preferred places. Foursquare provides a ranking of urban spaces and venues related to tourism, and the location of the tweets confirms the seasonal nature of Benidorm. Despite the fact that information from location-based social media has to be treated carefully, since each service has its own unique purpose, the method proposed has proven to be effective and reliable to depict a representative sample of people’s social patterns and preferences in tourist cities

STRATEGY TO PROMOTE LOCATION SHARING ON SOCIAL NETWORK UNDER PERSPECTIVES OF CULTURE

The increasing number of smartphone which are pre-equipped GPS module and ability to install social network applications makes a better chance than ever to combine and exploiting the advantages of location-based technologies and social network. By using these technologies, users not only share their locations on social network but also get useful information from friends which could indirectly promote for their locations and their services. Promoting location sharing becomes an indispensable part of social network which may bring a great business opportunity. However, user from different cultures tend to have different location sharing behaviors, therefore the performance of business models of location sharing on social network are also distinctive. Thus, the purpose of this study is to investigate the role of culture in location sharing behavior among social network users by answering the question of the role of benefits, trust, and social influence on attitude to share the location information.Moreover, this study try to evaluate the impact of incentive given to the user by sharing appointed location and the impact of positive feedback on location sharing behavior

An Analysis on the Spatial Characteristics of Satisfaction on the Residential Environment Using Tweets

The purpose of this study is to analyze the regional difference of spatial distribution of residential satisfaction by extracting the elements of residential satisfaction in the text of tweet data. We determined three themes such as “safety”, “amenity” and “convenience”, base search terms by theme. And we detailed the search terms by base search term in order to retrieve the tweets related to the satisfaction of residential environments. We analyzed the selected tweets and visualized the results of analysis on the map and then investigated the satisfaction of residential environments through the index analysis which was a proportion of tweet ratio of theme to whole tweet ratio by region This study shows that it may replace the offline survey method by the analysis of tweets on SNS in investigating the satisfaction of residential environments by regions in South Korea

Advancing Science with VGI: Reproducibility and Replicability of Recent Studies using VGI

In scientific research, reproducibility and replicability are requirements to ensure the advancement of our body of knowledge. T his holds true also for VGI - related research and studies. However, the characteristics of VGI suggest particular difficulties in ensuring reproducibility and replicability . In this paper, we aim to examine the current situation in VGI - related research , and identify strategies to ensure realization of its full potential. To do so, we first investigate the different aspects of reprod ucibility and replicability and their impact on VGI - related research . These impacts are different depending on the objectives of the study. Therefore , we examine the study focus of VGI - related research to assess the current body of research and structure o ur assessment . Th is work is based on a rigorous review of the elements of reproducibility and a systematic mapping and analysis of 58 papers on the use of VGI in the crisis management field. Results of our investigation show that reproducibility issues related to data are a serious concern , while reproducibility issues related to analysis methods and processes face fewer challenges. Howe ver, since most studies still focus on analyzing the source data, reproducibility and replicability are still an unsolved problem in VGI - related research. Therefore, we show initiative s tackling the problem, and finally formulate strategies to improve the situatio

Reading the social preferences of tourist destinations through social media data

The social preferences of individuals have been traditionally identified through traditional means using field techniques such as direct interviewing, observation and people-counting. The virtual layer of the social system currently allows new ways to identify the most preferred urban areas or venues. With that in mind, this paper aims to study how data from two Location-Based Social Networks: Foursquare and Twitter can shed light on empirical and theoretical observations about the spatial patterns characterizing where people tend to be and socialise in a tourist city. The methodology proposed consists of three stages. First, a self-developed desktop application retrieves geospatial data from the selected social networks. Then, the dataset obtained is organised and sorted. Finally, the georeferenced data is visualised and analysed and the trends are noted and discussed. To that end, the city of Benidorm was selected as a case study and the data was collected during the off-peak tourist season. The results demonstrate a correlation between the empirical assumptions and the findings from the social networks analysis about people’s preferred places. Foursquare provides a ranking of urban spaces and venues related to tourism, and the location of the tweets confirms the seasonal nature of Benidorm. Despite the fact that information from location-based social media has to be treated carefully, since each service has its own unique purpose, the method proposed has proven to be effective and reliable to depict a representative sample of people’s social patterns and preferences in tourist cities

Beyond data collection: Objectives and methods of research using VGI and geo-social media for disaster management

This paper investigates research using VGI and geo-social media in the disaster management context. Relying on the method of systematic mapping, it develops a classification schema that captures three levels of main category, focus, and intended use, and analyzes the relationships with the employed data sources and analysis methods. It focuses the scope to the pioneering field of disaster management, but the described approach and the developed classification schema are easily adaptable to different application domains or future developments. The results show that a hypothesized consolidation of research, characterized through the building of canonical bodies of knowledge and advanced application cases with refined methodology, has not yet happened. The majority of the studies investigate the challenges and potential solutions of data handling, with fewer studies focusing on socio-technological issues or advanced applications. This trend is currently showing no sign of change, highlighting that VGI research is still very much technology-driven as opposed to theory- or application-driven. From the results of the systematic mapping study, the authors formulate and discuss several research objectives for future work, which could lead to a stronger, more theory-driven treatment of the topic VGI in GIScience.Carlos Granell has been partly funded by the Ramón y Cajal Programme (grant number RYC-2014-16913

Analysing successful public spaces in an urban street network using data from the social networks Foursquare and Twitter

This paper analyzes success public spaces (specifically plazas) in the urban fabric of the city of Murcia, Spain. Two approaches were adopted. Firstly, the city was visualized as a complex network whose nodes represent plazas. A centrality algorithm was applied to determine the importance of each node. Secondly, data sets were used from social networks Foursquare and Twitter, which provide different types of data as well as user profiles. Foursquare data indicates user preferences of urban public spaces, while in this respect Twitter offers less specific user generated data. Both perspectives have facilitated two rankings based on the most visited plazas in the city. The results enabled a comparative study to determine the potential differences or similarities between both approaches.This work was partially supported by Spanish Govern, Ministerio de Economía y Competividad, grant number TIN2014-53855-P