Social Media Geographic Information Research Articles

Follow the Geographic Information: The Challenges of Spatial Analysis in Digital Methods

In the digital environment, defined as a space with no anchors (Menduni 2014), the spatial dimension may have a significant role, mostly in relation to the Internet or digital studies. Social Media Geographic Information (Campagna et al. 2016), even if limited, can be highly useful to overcome some limitations of social media analysis and user generated content. With the objective to report the potential and limits of this approach, in this article a case study will be presented on the individual perception related to COVID-19 in Italy. Starting from the analysis of ecological data and the social media data, we reproduce three measures by exploring three different elements that could be anchored to a geographical dimension: the storytelling of COVID (COVID-Issues), the spread of infection (COVID-Spread), and the distribution of measures (COVID-Measures) to understand the regional trends of the second wave of the pandemic emergence that represent the timespan of this contribution. Keywords: geo-social media, twitter, ecological analysis, case study, API

SEMANTIC VALIDATION OF SOCIAL MEDIA GEOGRAPHIC INFORMATION: A CASE STUDY ON INSTAGRAM DATA FOR EXPO MILANO 2015

Abstract. Social media data, such as Instagram posts, can be associated with spatial positions. This information can be exploited to perform spatial analyses, such as identifying distribution patterns of points representing the positions of social media users during an emergency or while attending a specific event or exhibition. However, the geolocation provided by Social Media Geographic Information (SMGI) needs to be validated, in order for the spatial data to be used in a meaningful way in subsequent spatial analyses or mapping procedures. In this paper, a case study is presented based on Instagram data collected during the first two months of the Expo Milano 2015 exhibition, where the spatial data have been validated by exploiting the semantic component of the posts.

OPPORTUNITIES FOR AN EFFECTIVE USE OF SOCIAL MEDIA GEOGRAPHIC INFORMATION (SMGI) WITHIN GEODESIGN APPROACH

This contribution focuses on two types of georeferenced User-Generated Content (geo-UGC): Volunteered Geographic Information (VGI) and Social Media Geographic Information (SMGI): both can be proftably used in spatial planning practices, thanks to the high potential of the information they enclose. Several case studies, developed by the authors, are presented to illustrate how geo-UGC can be used in different stages of spatial planning processes, supporting a more multifaceted understanding of places, contributing to more participatory processes, and fostering the collaboration between decision-makers in spatial planning practices. The Geodesign approach has been used as a base framework to underpin the discussion. In addition, the case studies show how geo-UGC can be advantageous in knowledge building on the current regional and urban dynamics, in identifying possible alternatives and in fnding agreement on preferred future developments.

BIG-DATA TO SUPPORT THE STUDY OF THE ENVIRONMENTAL DISASTER IN MARIANA, MG: FROM VGI TO SOCIAL MEDIA GEOGRAPHIC INFORMATION

The use of Social Media Geographic Information in a planning process would improve our knowledge about local values, urban and landscape development and could support decision-making. This paper presents a case study of an environmental disaster that happened recently in one of the most important social economic areas in Brazil to understand how this type of information could be used as a systematized planning input. The authors seek to understand if it is possible to use VGI and SMGI (Volunteered Geographic Information and Social Media Geographic Information) to capture social values, such as genius loci (the essence of the place)and expectations, the values that should be considered in a disaster recovery plan. To do that, we tested an active VGI platform and passive SMGI posts' analysis. Our best results so far relied on a proposal for image analysis from Instagram posts to separate them in the themes of "everyday life", "landscape" and "memes". Presenting a logic and a tool to do this classification automatically, we provide a first step to be used in big-data, as they are characterized by a big amount of data, and we can develop a first analysis in the main pictures posted by people from that area. It is a contribution to use social media to measure values and collective expectations from a place.

Social Media Geographic Information: Recent Findings and Opportunities for Smart Spatial Planning

This paper deals with the opportunities of Social Media Geographic Information (SMGI) as valuable support for analysis, design and decision-making in urban and regional planning. In the light of the recent advances in digital geographic information, such as Spatial Data Infrastructures (SDI) and Volunteered Geographic Information (VGI) which are fostering innovation in urban and regional planning, the authors focus on the potentialities of Social Media as source of knowledge for the planning practices. The authors argue SMGI may play an important role to inform 'smart city' strategies extending authoritative and sensor data infrastructure with experiential and pluralist citizens knowledge. To support this thesis, an innovative methodology for the advance of Social Media Geographic Information (SMGI) Analytics is proposed. To this end, the authors present an original user-friendly tool able to extract information from popular Social Media such as Twitter.com and Youtube.com and to apply Spatial-Temporal Textual (STTx) analysis . Some examples are provided at the regional and at the local scale in order to demonstrate the potential of SMGI analytics in regional and urban planning. The results show how SMGI analytics can support design, analysis and decision making in planning, and add the value of pluralism to inform smart city initiatives. The paper ends with some brief conclusions on the opportunities of SMGI analytics for possibly affecting decision-making dynamics and urban and regional planning processes, through citizens’ dialogue and integration of experiential and professional knowledge.