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The presented study aims to investigate the relationship between the use of emojis in location-based social media and the location of the corresponding post in terms of perceived objects and conducted activities connected to this place. The basis for this is not a purely frequency-based assessment, but a specifically introduced measure called typicality. To evaluate the typicality measure and examine the assumption that emojis are contextual indicants, a dataset of worldwide geotagged posts from Instagram relating to sunset and sunrise events is used, converted to a privacy-aware version based on a Hyperloglog approach. Results suggest that emojis can often provide more nuanced information about user activities and the surrounding environment than is possible with hashtags. Thus, emojis may be suitable for identifying less obvious characteristics and the sense of a place. Emojis are already explored in research, but mainly for sentiment analysis, for semantic studies or as part of emoji prediction. In contrast, this work provides novel insights into the user’s spatial or activity context by applying the typicality measure and therefore considers emojis contextual indicants.
Eva Hauthal; Alexander Dunkel; Dirk Burghardt. Emojis as Contextual Indicants in Location-Based Social Media Posts. ISPRS International Journal of Geo-Information 2021, 10, 407 .
AMA StyleEva Hauthal, Alexander Dunkel, Dirk Burghardt. Emojis as Contextual Indicants in Location-Based Social Media Posts. ISPRS International Journal of Geo-Information. 2021; 10 (6):407.
Chicago/Turabian StyleEva Hauthal; Alexander Dunkel; Dirk Burghardt. 2021. "Emojis as Contextual Indicants in Location-Based Social Media Posts." ISPRS International Journal of Geo-Information 10, no. 6: 407.
Emotionen, Gefühle, vergangene Erfahrungen, die eigene Identität und soziale Interaktionen beeinflussen, wie wir Landschaft wahrnehmen und wertschätzen. Wahrgenommene Werte von Landschaften variieren daher ganz grundlegend zwischen verschiedenen Menschen. Aus diesem Grund definiert beispielsweise die Europäische Landschaftskonvention Landschaft „as a zone or area as perceived by local people or visitors“ (ELC art. 1, para. 38). Für anwendungsorientierte Disziplinen wie die Landschaftsplanung bedeutet dies oft eine große Herausforderung. Informationen darüber, wie Landschaft durch viele Menschen wahrgenommen wird sind entweder nur aufwendig zu beschaffen oder schlichtweg nicht verfügbar. Die hier vorgestellte Visualisierungsmethode von ‚Tag Maps‘ nutzt Daten aus Sozialen Medien als neue Informationsquelle, um subjektive Wert- und Bedeutungszuschreibungen von vielen Menschen darzustellen. Die Grafiken sind besonders geeignet, um Gemeinsamkeiten der Wahrnehmung vieler Menschen kartografisch auszuwerten. Die Ergebnisse können als zusätzliche Informationsquelle genutzt werden, um Planungsentscheidungen auf eine breitere, repräsentativere Basis zu stellen. Aufgrund der Generalisierung sind der Interpretation von Tag Maps Grenzen gesetzt, welche im Abschluss diskutiert werden. Betont wird die Bedeutung der vorgestellten Methode als Ausgangspunkt für weiterführende aktive Beteiligung und Diskussion von und mit der Bevölkerung.
Alexander Dunkel. Tag Maps in der Landschaftsplanung. Handbuch Methoden Visueller Kommunikation in der Räumlichen Planung 2021, 137 -166.
AMA StyleAlexander Dunkel. Tag Maps in der Landschaftsplanung. Handbuch Methoden Visueller Kommunikation in der Räumlichen Planung. 2021; ():137-166.
Chicago/Turabian StyleAlexander Dunkel. 2021. "Tag Maps in der Landschaftsplanung." Handbuch Methoden Visueller Kommunikation in der Räumlichen Planung , no. : 137-166.
Social media data is heavily used to analyze and evaluate situations in times of disasters, and derive decisions for action from it. In these critical situations, it is not surprising that privacy is often considered a secondary problem. In order to prevent subsequent abuse, theft or public exposure of collected datasets, however, protecting the privacy of social media users is crucial. Avoiding unnecessary data retention is an important question that is currently largely unsolved. There are a number of technical approaches available, but their deployment in disaster management is either impractical or requires special adaption, limiting its utility. In this case study, we explore the deployment of a cardinality estimation algorithm called HyperLogLog into disaster management processes. It is particularly suited for this field, because it allows to stream data in a format that cannot be used for purposes other than the originally intended. We develop and conduct a focus group discussion with teams of social media analysts. We identify challenges and opportunities of working with such a privacy-enhanced social media data format and compare the process with conventional techniques. Our findings show that, with the exception of training scenarios, deploying HyperLogLog in the data acquisition process will not distract the data analysis process. Instead, several benefits, such as improved working with huge datasets, may contribute to a more widespread use and adoption of the presented technique, which provides a basis for a better integration of privacy considerations in disaster management.
Marc Löchner; Ramian Fathi; David Schmid; Alexander Dunkel; Dirk Burghardt; Frank Fiedrich; Steffen Koch. Case Study on Privacy-aware Social Media Data Processing in Disaster Management. ISPRS International Journal of Geo-Information 2020, 9, 709 .
AMA StyleMarc Löchner, Ramian Fathi, David Schmid, Alexander Dunkel, Dirk Burghardt, Frank Fiedrich, Steffen Koch. Case Study on Privacy-aware Social Media Data Processing in Disaster Management. ISPRS International Journal of Geo-Information. 2020; 9 (12):709.
Chicago/Turabian StyleMarc Löchner; Ramian Fathi; David Schmid; Alexander Dunkel; Dirk Burghardt; Frank Fiedrich; Steffen Koch. 2020. "Case Study on Privacy-aware Social Media Data Processing in Disaster Management." ISPRS International Journal of Geo-Information 9, no. 12: 709.
Through volunteering data, people can help assess information on various aspects of their surrounding environment. Particularly in natural resource management, Volunteered Geographic Information (VGI) is increasingly recognized as a significant resource, for example, supporting visitation pattern analysis to evaluate collective values and improve natural well-being. In recent years, however, user privacy has become an increasingly important consideration. Potential conflicts often emerge from the fact that VGI can be re-used in contexts not originally considered by volunteers. Addressing these privacy conflicts is particularly problematic in natural resource management, where visualizations are often explorative, with multifaceted and sometimes initially unknown sets of analysis outcomes. In this paper, we present an integrated and component-based approach to privacy-aware visualization of VGI, specifically suited for application to natural resource management. As a key component, HyperLogLog (HLL)—a data abstraction format—is used to allow estimation of results, instead of more accurate measurements. While HLL alone cannot preserve privacy, it can be combined with existing approaches to improve privacy while, at the same time, maintaining some flexibility of analysis. Together, these components make it possible to gradually reduce privacy risks for volunteers at various steps of the analytical process. A specific use case demonstration is provided, based on a global, publicly-available dataset that contains 100 million photos shared by 581,099 users under Creative Commons licenses. Both the data processing pipeline and resulting dataset are made available, allowing transparent benchmarking of the privacy–utility tradeoffs.
Alexander Dunkel; Marc Löchner; Dirk Burghardt. Privacy-Aware Visualization of Volunteered Geographic Information (VGI) to Analyze Spatial Activity: A Benchmark Implementation. ISPRS International Journal of Geo-Information 2020, 9, 607 .
AMA StyleAlexander Dunkel, Marc Löchner, Dirk Burghardt. Privacy-Aware Visualization of Volunteered Geographic Information (VGI) to Analyze Spatial Activity: A Benchmark Implementation. ISPRS International Journal of Geo-Information. 2020; 9 (10):607.
Chicago/Turabian StyleAlexander Dunkel; Marc Löchner; Dirk Burghardt. 2020. "Privacy-Aware Visualization of Volunteered Geographic Information (VGI) to Analyze Spatial Activity: A Benchmark Implementation." ISPRS International Journal of Geo-Information 9, no. 10: 607.
Social media platforms such as Twitter are extensively used for expressing and exchanging thoughts, opinions, ideas, and feelings, i.e., reactions concerning a topic or an event. Factual information about an event to which people are reacting can be obtained from different types of (geo-)sensors, official authorities, or the public press. However, these sources hardly reveal the emotional or attitudinal impact of events on people, which is, for example, reflected in their reactions on social media. Two approaches that utilize emojis are proposed to obtain the sentiment and emotions contained in social media reactions. Subsequently, these two approaches, along with visualizations that focus on space, time, and topic, are applied to Twitter reactions in the example case of Brexit.
Eva Hauthal; Dirk Burghardt; Alexander Dunkel. Analyzing and Visualizing Emotional Reactions Expressed by Emojis in Location-Based Social Media. ISPRS International Journal of Geo-Information 2019, 8, 113 .
AMA StyleEva Hauthal, Dirk Burghardt, Alexander Dunkel. Analyzing and Visualizing Emotional Reactions Expressed by Emojis in Location-Based Social Media. ISPRS International Journal of Geo-Information. 2019; 8 (3):113.
Chicago/Turabian StyleEva Hauthal; Dirk Burghardt; Alexander Dunkel. 2019. "Analyzing and Visualizing Emotional Reactions Expressed by Emojis in Location-Based Social Media." ISPRS International Journal of Geo-Information 8, no. 3: 113.
Events are a core concept of spatial information, but location-based social media (LBSM) provide information on reactions to events. Individuals have varied degrees of agency in initiating, reacting to or modifying the course of events, and reactions include observations of occurrence, expressions containing sentiment or emotions, or a call to action. Key characteristics of reactions include referent events and information about who reacted, when, where and how. Collective reactions are composed of multiple individual reactions sharing common referents. They can be characterized according to the following dimensions: spatial, temporal, social, thematic and interlinkage. We present a conceptual framework, which allows characterization and comparison of collective reactions. For a thematically well-defined class of event such as storms, we can explore differences and similarities in collective attribution of meaning across space and time. Other events may have very complex spatio-temporal signatures (e.g. political processes such as Brexit or elections), which can be decomposed into series of individual events (e.g. a temporal window around the result of a vote). The purpose of our framework is to explore ways in which collective reactions to events in LBSM can be described and underpin the development of methods for analysing and understanding collective reactions to events.
Alexander Dunkel; Gennady Andrienko; Natalia Andrienko; Dirk Burghardt; Eva Hauthal; Ross Purves. A conceptual framework for studying collective reactions to events in location-based social media. International Journal of Geographical Information Science 2018, 33, 780 -804.
AMA StyleAlexander Dunkel, Gennady Andrienko, Natalia Andrienko, Dirk Burghardt, Eva Hauthal, Ross Purves. A conceptual framework for studying collective reactions to events in location-based social media. International Journal of Geographical Information Science. 2018; 33 (4):780-804.
Chicago/Turabian StyleAlexander Dunkel; Gennady Andrienko; Natalia Andrienko; Dirk Burghardt; Eva Hauthal; Ross Purves. 2018. "A conceptual framework for studying collective reactions to events in location-based social media." International Journal of Geographical Information Science 33, no. 4: 780-804.
Alexander Dunkel. Visualizing the perceived environment using crowdsourced photo geodata. Landscape and Urban Planning 2015, 142, 173 -186.
AMA StyleAlexander Dunkel. Visualizing the perceived environment using crowdsourced photo geodata. Landscape and Urban Planning. 2015; 142 ():173-186.
Chicago/Turabian StyleAlexander Dunkel. 2015. "Visualizing the perceived environment using crowdsourced photo geodata." Landscape and Urban Planning 142, no. : 173-186.