An empirical investigation of attitude towards location-aware social network service

Kofod-Petersen, Anders; Gransaether, P.A.; Krogstie, John

doi:10.1504/ijmc.2010.030520

Cited by 24 publications

(15 citation statements)

References 16 publications

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“…Hence, unreasonable expectations may lead to invoice amounts which are perceived as unexpectedly high or even shocking (Gerpott 2007). Results of Bauer et al (2008) and Kofod-Petersen et al (2010) indicate that perceived risks of excessive invoicing amounts have a significantly negative effect on the willingness to use LBS. Put differently, we posit: H5: The extent of perceived LBS specific risk of excessive invoicing amounts has a negative effect on the willingness to use LBS.…”

Section: Development Of Hypothesesmentioning

confidence: 98%

“…Another risk category that is intensely discussed in the context of LBS deals with concerns of customers that LBS providers may collect more personal information than technologically required, generate defective personal data and/or misuse personal data for other purposes than LBS delivery or that third parties gain unauthorized data access (Smith et al 1996). Past empirical LBS research overwhelmingly concludes that high perceived data privacy risks form an important LBS usage barrier (Junglas and Spitzmüller 2006;Sheng et al 2008;Lee et al 2009;Tsai et al 2009;Kofod-Petersen et al 2010). Thus, we test: H8: The level of perceived LBS specific data privacy risks has a negative impact on the willingness to use LBS.…”

Section: Development Of Hypothesesmentioning

confidence: 99%

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Determinants of the Willingness to Use Mobile Location-Based Services

Gerpott

Berg

2011

Bus Inf Syst Eng

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Section: Development Of Hypothesesmentioning

confidence: 98%

Section: Development Of Hypothesesmentioning

confidence: 99%

Determinants of the Willingness to Use Mobile Location-Based Services

Gerpott

Berg

2011

Bus Inf Syst Eng

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“…Participants use a mobile phone for five days and share their location by text message upon request from the other participants. Kofod-Petersen et al [23] deploy a location-sharing system over three weeks in a three-storey building during a cultural festival. 1,661 participants use ultrasound tags to be located, and several terminals are also distributed throughout the building.…”

Section: Application Deploymentmentioning

confidence: 99%

Reliable Online Social Network Data Collection

Abdesslem

Parris

Henderson

2012

Computational Social Networks

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Large quantities of information are shared through online social networks, making them attractive sources of data for social network research. When studying the usage of online social networks, these data may not describe properly users' behaviours. For instance, the data collected often include content shared by the users only, or content accessible to the researchers, hence obfuscating a large amount of data that would help understanding users' behaviours and privacy concerns. Moreover, the data collection methods employed in experiments may also have an effect on data reliability when participants self-report inacurrate information or are observed while using a simulated application. Understanding the effects of these collection methods on data reliability is paramount for the study of social networks; for understanding user behaviour; for designing socially-aware applications and services; and for mining data collected from such social networks and applications. This chapter reviews previous research which has looked at social network data collection and user behaviour in these networks. We highlight shortcomings in the methods used in these studies, and introduce our own methodology and user study based on the Experience Sampling Method; we claim our methodology leads to the collection of more reliable data by capturing both those data which are shared and not shared. We conclude with suggestions for collecting and mining data from online social networks.

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“…FindMyFriends is a place-centred location-aware social network system that was installed during a three week student festival in Trondheim, Norway [12]. In brief, this system offered the potential of keeping track of your friends in the main venue of the festival.…”

Section: Privacy In Location-aware Social-networkmentioning

confidence: 99%

“…In addition, only 9.7 % would use a functionality to lie about one's position if it had been implemented. Finally, 55 % reported that they would use a similar system on a city-wide scale (for a more thorough analysis see [12]). Taken together, these findings suggest that users find the benefits of such a system outweigh any negative aspects.…”

Section: Privacy In Location-aware Social-networkmentioning

confidence: 99%

Minimising Information Asymmetry by Using Proxies

Kofod-Petersen

2010

2010 International Conference on Complex, Intelligent and Software Intensive Systems

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The fast growing number of social-network services utilising location information has also increased the interest in privacy for such systems. Many interesting ideas and proposals have appeared. One of the most interesting is perhaps the notion of minimising asymmetry of information flow. This idea can also be applied in the area of ambient assisted living. The work described here reports on some initiatives on location-aware systems and ambient assisted living. The combined experiences gained from these projects have led to the development of a model for minimising asymmetry by proxies in an ambient assisted living environment.

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An empirical investigation of attitude towards location-aware social network service

Cited by 24 publications

References 16 publications

Determinants of the Willingness to Use Mobile Location-Based Services

Determinants of the Willingness to Use Mobile Location-Based Services

Reliable Online Social Network Data Collection

Minimising Information Asymmetry by Using Proxies

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