Marius, the giraffe

Zimmerman, Chris; Chen, Yuran; Hardt, Daniel; Vatrapu, Ravi

doi:10.1145/2631488.2631501

Cited by 9 publications

(2 citation statements)

References 33 publications

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“…Also, major international media has also participated in the case of Marius. British BBC and The Guardian newspaper has also referred to the killing, CNN followed the case on both network and TV, and The New York Times has also written about Marius' death [71].…”

Section: Case Study 2: Social Set Analysis Of Corporate Social Media ...mentioning

confidence: 99%

Social Set Analysis: A Set Theoretical Approach to Big Data Analytics

et al. 2016

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Current analytical approaches in computational social science can be characterized by four dominant paradigms: text analysis (information extraction and classification), social network analysis (graph theory), social complexity analysis (complex systems science), and social simulations (cellular automata and agent-based modeling). However, when it comes to organizational and societal units of analysis, there exists no approach to conceptualize, model, analyze, explain, and predict social media interactions as individuals' associations with ideas, values, identities, and so on. To address this limitation, based on the sociology of associations and the mathematics of set theory, this paper presents a new approach to big data analytics called social set analysis. Social set analysis consists of a generative framework for the philosophies of computational social science, theory of social data, conceptual and formal models of social data, and an analytical framework for combining big social data sets with organizational and societal data sets. Three empirical studies of big social data are presented to illustrate and demonstrate social set analysis in terms of fuzzy set-theoretical sentiment analysis, crisp set-theoretical interaction analysis, and eventstudies-oriented set-theoretical visualizations. Implications for big data analytics, current limitations of the set-theoretical approach, and future directions are outlined.INDEX TERMS Big social data, formal models, social set analysis, big data visual analytics, new computational models for big social data.

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Section: Case Study 2: Social Set Analysis Of Corporate Social Media ...mentioning

confidence: 99%

Social Set Analysis: A Set Theoretical Approach to Big Data Analytics

et al. 2016

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“…For example, the naming of a giraffe was attributed internally at Copenhagen Zoo for the sensationalized media storm that followed its death (personal observation, Vicky Melfi). The negative ramifications of this were largely reported outside of Denmark (Zimmerman et al, 2014). This incident exemplifies how cultural differences and contradictory expectations of zoos can influence perceptions of HAI (Cohen & Fennell, 2016), from which keepers are likely not exempt (Birke et al, 2019).…”

Section: Discussionmentioning

confidence: 82%

Furred and feathered friends: How attached are zookeepers to the animals in their care?

et al. 2021

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Keeper-animal relationships (KARs) appear to be important in zoos, since they can enhance the well-being of both the animals and the keepers, can make animal husbandry easier, but conversely might risk inappropriate habituation of animals and possible risks to the safety of keepers. It is, therefore, important to know more about the variables involved in relationship formation. Here we use a modified version of the Lexington Attachment to Pets Scale (LAPS) to measure the strength of KARs between keepers and animals in their care, both in the zoo and in the home. LAPS questionnaires were completed by 187 keepers in 19 different collections across three countries. LAPS scores for attachment to zoo animals (ZA) were significantly lower than for pet animals (PA). There was no significant difference in ZA scores between different taxa, but there were significant taxon differences between PA scores. There were significant differences in both ZA and PA scores between different collections. Female respondents scored more highly than males for both ZA and PA. Multiple regression revealed that location, gender, and time spent with animals were significant predictors for ZA, while only gender and taxon were significant predictors for PA. It was concluded that PA scores were comparable with those for the general public, and reflected strong attachment of keepers to their pets, while ZA scores, although also reflecting attachment, were influenced by differences in institutional culture.

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Threat or treat for tourism organizations? The Copenhagen Zoo social media storm

Rydén

Kottika

Hossain

et al. 2019

Journal of Tourism Research

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Social media have emerged as a game changer for tourism by empowering consumers to collectively approve or oppose organizational behaviors. When consumers rise against organizations, social media storms (SMSs) can be an outcome. This research proposes a conceptual framework to help tourism organizations understand SMSs and to guide more effective decision making. Contextualized by a case study of the Copenhagen Zoo, it is shown how and why SMSs are an expression of negative consumer empowerment that brings challenges as well as opportunities. As demonstrated, an SMS can lead to a helix for value creation for the organization, consumers, and society. KEYWORDSSocial media storm (SMS); tourist attraction branding; consumer empowerment; negative customer emotions; marketing management; Copenhagen Zoo 1 | INTRODUCTION Social media have profoundly impacted tourism and marketing (Leung, Law, van Hoof, & Buhalis, 2013) by fundamentally changing the way organizations interact with customers. Booking sites have diminished the role of travel agents as consumers can plan their holidays more expediently, conveniently, and cheaply. Social media and sites based on customer reviews, like TripAdvisor, have gained momentum (Oriade & Robinson, 2019). Tourism organizations may benefit from their global range, but Wee (2017) warns organizations and researchers not to ignore the role of social media as they enable consumers to become critics in their own rights. Though social media communication strongly impacts tourism firms and tourist decision-making (Moro and Rita, 2018), it is scarcely investigated in tourism research.This research aims to fill this void by showing why consumer empowerment in the tourism sector is not only realized through online consumer-centric marketing (Niininen, Buhalis, & March, 2007), but also by openly sharing opinions, attitudes, and emotions towards service providers. While consumers embrace the empowerment, organizations struggle to manage the process (Shankar, Cherrier & Caniford, 2006). In an increasing number of cases, negative emotions having retaliatory intent and anger (Grégoire & Fisher, 2008) accumulate on social media, and are being referred to as social media storms (SMSs).An SMS refers to a sudden and explosive social media dissemination of negative consumer emotion towards an organization (Pfeffer, Zorbach, & Carley, 2014). Consumer empowerment is defined as a state of mind, often accompanied by a physical act, which enables consumers to push through their needs, wants, and demands with other individuals or organizations in the marketplace (Pires,

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Marius, the giraffe

Cited by 9 publications

References 33 publications

Social Set Analysis: A Set Theoretical Approach to Big Data Analytics

Social Set Analysis: A Set Theoretical Approach to Big Data Analytics

Furred and feathered friends: How attached are zookeepers to the animals in their care?

Threat or treat for tourism organizations? The Copenhagen Zoo social media storm

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