Abstract
Social Software Engineering is a new field
of study that aims to identify how social aspects interact and affect the
design of software during the software development cycle. The identification of
social parameters and criteria that affect the elicitation of technical,
functional and non-functional requirements is a critical step for the system to
be. Protecting users’ privacy on the other hand, is also critical since users
tend to utilize services and applications they trust especially regarding the
manipulation and handling of their personal information. At the same time users
are inclined to express their privacy concerns regarding mobile applications
that store and disseminate various privacy related information e.g. geolocation
data. The social parameters and social criteria which are indicative for
setting requirements and designing software focusing on privacy issues by
previous literature, are explored, focusing on users’ social identity and
geolocation data in social media. Drawing on Social, Information and
Communication and Geolocation Theories, users’ special characteristics of
social identity- multiplicity, permeability and overlapping- will be explored,
as well as their possible revealing information by utilizing geolocation
services - space of actions, frames-, in order to identify users’ faces in this
field. This work aims to broaden understanding of users’ digital identities and
geolocation data impact through an interdisciplinary approach, on the setting
of requirements elicitation and modelling approaches for designing
privacy-aware systems.
Keywords
References
- Abbattista, F., Calefato, F., Gendarmi, D., & Lanubile, F. (2008). Incorporating social software into distributed agile development environments. In Proceedings of the 23rd IEEE/ACM International Conference on Automated Software Engineering (pp. II–46). IEEE Press. Retrieved from http://dl.acm.org/citation.cfm?id=3107639Balicki, J., WSEAS (Organization), International Conference on Artificial Intelligence, K. E. and D. B., IEEE International Conference on Fuzzy Systems, & IEEE International Conference on Neural Networks (Eds.). (2014). Advances in neural networks, fuzzy systems and artifical intelligence: Proceedings of the 13th International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (AIKED ’14) ; Proceedings of the 15th International Conference on Fuzzy Systems (FS ’14) ; Proceedings of the 15th International Conference on Neural Networks (NN ’14) : Gdansk, Poland, May 15-17, 2014.Barkhuus, L., & Dey, A. K. (2003). Location-Based Services for Mobile Telephony: a Study of Users’ Privacy Concerns. In Interact (Vol. 3, pp. 702–712).Beresford, A. R., & Stajano, F. (2003). Location privacy in pervasive computing. IEEE Pervasive Computing, 2(1), 46–55. https://doi.org/10.1109/MPRV.2003.1186725Bettini, C., Wang, X. S., & Jajodia, S. (2005). Protecting privacy against location-based personal identification. In Workshop on Secure Data Management (pp. 185–199). Springer.Consolvo, S., Smith, I. E., Matthews, T., LaMarca, A., Tabert, J., & Powledge, P. (2005). Location disclosure to social relations: why, when, & what people want to share. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 81–90). ACM.Cramer, H., Rost, M., & Holmquist, L. E. (2011). Performing a check-in: emerging practices, norms and’conflicts’ in location-sharing using foursquare. In Proceedings of the 13th international conference on human computer interaction with mobile devices and services (pp. 57–66). ACM.Duckham, M., & Kulik, L. (2005). A Formal Model of Obfuscation and Negotiation for Location Privacy. In Pervasive Computing (pp. 152–170). Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428572_10Duckham, M., & Kulik, L. (2006). Location privacy and location-aware computing. Dynamic & Mobile GIS: Investigating Change in Space and Time, 3, 35–51.Fabio Massacci, Marco Prest and Nicola Zannone. (200AD). USING A SECURITY REQUIREMENTS ENGINEERING METHODOLOGY IN PRACTICE: THE COMPLIANCE WITH THE ITALIAN DATA PROTECTION LEGISLATION.Jenkins, R. (2008). Social identity (3rd ed). London ; New York: Routledge.Lahlou, S. (2008). Identity, social status, privacy and face-keeping in digital society. Social Science Information, 47(3), 299–330. https://doi.org/10.1177/0539018408092575Liu, L. (2007). From data privacy to location privacy: models and algorithms. In Proceedings of the 33rd international conference on Very large data bases (pp. 1429–1430). VLDB Endowment.Miguel, C., & Medina, P. (2011). The Transformation of Identity and Privacy through Online Social Networks (The CouchSurfing case). Retrieved from http://eprints.leedsbeckett.ac.uk/2159/1/The%20Transformation%20of%20Identity%20and%20Privacy_The%20CouchSurfing%20Case.pdfMyles, G., Friday, A., & Davies, N. (2003). Preserving privacy in environments with location-based applications. IEEE Pervasive Computing, 2(1), 56–64.Nario-Redmond, M. R., Biernat, M., Eidelman, S., & Palenske, D. J. (2004). The Social and Personal Identities Scale: A Measure of the Differential Importance Ascribed to Social and Personal Self-Categorizations. Self and Identity, 3(2), 143–175. https://doi.org/10.1080/13576500342000103Nicola Zannone, Fabio Massacci, & and John Mylopoulos. (2006). Security Requirements Engineering Methodologies.ppt. Department of Information and Communication Technology University of Trento.Schwartz, R., & Halegoua, G. R. (2015). The spatial self: Location-based identity performance on social media. New Media & Society, 17(10), 1643–1660.Shokri, R., Theodorakopoulos, G., Boudec, J. Y. L., & Hubaux, J. P. (2011). Quantifying Location Privacy. In 2011 IEEE Symposium on Security and Privacy (pp. 247–262). https://doi.org/10.1109/SP.2011.18Snekkenes, E. (2001). Concepts for Personal Location Privacy Policies. In Proceedings of the 3rd ACM Conference on Electronic Commerce (pp. 48–57). New York, NY, USA: ACM. https://doi.org/10.1145/501158.501164Tang, K. P., Lin, J., Hong, J. I., Siewiorek, D. P., & Sadeh, N. (2010). Rethinking location sharing: exploring the implications of social-driven vs. purpose-driven location sharing. In Proceedings of the 12th ACM international conference on Ubiquitous computing (pp. 85–94). ACM.
Abstract
Social Software Engineering is a new field of study that aims to identify how social aspects interact and affect the design of software during the software development cycle. The identification of social parameters and criteria that affect the elicitation of technical, functional and non-functional requirements is a critical step for the system to be. Protecting users’ privacy on the other hand, is also critical since users tend to utilize services and applications they trust especially regarding the manipulation and handling of their personal information. At the same time users are inclined to express their privacy concerns regarding mobile applications that store and disseminate various privacy related information e.g. geolocation data. The social parameters and social criteria which are indicative for setting requirements and designing software focusing on privacy issues by previous literature, are explored, focusing on users’ social identity and geolocation data in social media. Drawing on Social, Information and Communication and Geolocation Theories, users’ special characteristics of social identity- multiplicity, permeability and overlapping- will be explored, as well as their possible revealing information by utilizing geolocation services - space of actions, frames-, in order to identify users’ faces in this field. This work aims to broaden understanding of users’ digital identities and geolocation data impact through an interdisciplinary approach, on the setting of requirements elicitation and modelling approaches for designing privacy-aware systems.
References
- Abbattista, F., Calefato, F., Gendarmi, D., & Lanubile, F. (2008). Incorporating social software into distributed agile development environments. In Proceedings of the 23rd IEEE/ACM International Conference on Automated Software Engineering (pp. II–46). IEEE Press. Retrieved from http://dl.acm.org/citation.cfm?id=3107639Balicki, J., WSEAS (Organization), International Conference on Artificial Intelligence, K. E. and D. B., IEEE International Conference on Fuzzy Systems, & IEEE International Conference on Neural Networks (Eds.). (2014). Advances in neural networks, fuzzy systems and artifical intelligence: Proceedings of the 13th International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (AIKED ’14) ; Proceedings of the 15th International Conference on Fuzzy Systems (FS ’14) ; Proceedings of the 15th International Conference on Neural Networks (NN ’14) : Gdansk, Poland, May 15-17, 2014.Barkhuus, L., & Dey, A. K. (2003). Location-Based Services for Mobile Telephony: a Study of Users’ Privacy Concerns. In Interact (Vol. 3, pp. 702–712).Beresford, A. R., & Stajano, F. (2003). Location privacy in pervasive computing. IEEE Pervasive Computing, 2(1), 46–55. https://doi.org/10.1109/MPRV.2003.1186725Bettini, C., Wang, X. S., & Jajodia, S. (2005). Protecting privacy against location-based personal identification. In Workshop on Secure Data Management (pp. 185–199). Springer.Consolvo, S., Smith, I. E., Matthews, T., LaMarca, A., Tabert, J., & Powledge, P. (2005). Location disclosure to social relations: why, when, & what people want to share. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 81–90). ACM.Cramer, H., Rost, M., & Holmquist, L. E. (2011). Performing a check-in: emerging practices, norms and’conflicts’ in location-sharing using foursquare. In Proceedings of the 13th international conference on human computer interaction with mobile devices and services (pp. 57–66). ACM.Duckham, M., & Kulik, L. (2005). A Formal Model of Obfuscation and Negotiation for Location Privacy. In Pervasive Computing (pp. 152–170). Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428572_10Duckham, M., & Kulik, L. (2006). Location privacy and location-aware computing. Dynamic & Mobile GIS: Investigating Change in Space and Time, 3, 35–51.Fabio Massacci, Marco Prest and Nicola Zannone. (200AD). USING A SECURITY REQUIREMENTS ENGINEERING METHODOLOGY IN PRACTICE: THE COMPLIANCE WITH THE ITALIAN DATA PROTECTION LEGISLATION.Jenkins, R. (2008). Social identity (3rd ed). London ; New York: Routledge.Lahlou, S. (2008). Identity, social status, privacy and face-keeping in digital society. Social Science Information, 47(3), 299–330. https://doi.org/10.1177/0539018408092575Liu, L. (2007). From data privacy to location privacy: models and algorithms. In Proceedings of the 33rd international conference on Very large data bases (pp. 1429–1430). VLDB Endowment.Miguel, C., & Medina, P. (2011). The Transformation of Identity and Privacy through Online Social Networks (The CouchSurfing case). Retrieved from http://eprints.leedsbeckett.ac.uk/2159/1/The%20Transformation%20of%20Identity%20and%20Privacy_The%20CouchSurfing%20Case.pdfMyles, G., Friday, A., & Davies, N. (2003). Preserving privacy in environments with location-based applications. IEEE Pervasive Computing, 2(1), 56–64.Nario-Redmond, M. R., Biernat, M., Eidelman, S., & Palenske, D. J. (2004). The Social and Personal Identities Scale: A Measure of the Differential Importance Ascribed to Social and Personal Self-Categorizations. Self and Identity, 3(2), 143–175. https://doi.org/10.1080/13576500342000103Nicola Zannone, Fabio Massacci, & and John Mylopoulos. (2006). Security Requirements Engineering Methodologies.ppt. Department of Information and Communication Technology University of Trento.Schwartz, R., & Halegoua, G. R. (2015). The spatial self: Location-based identity performance on social media. New Media & Society, 17(10), 1643–1660.Shokri, R., Theodorakopoulos, G., Boudec, J. Y. L., & Hubaux, J. P. (2011). Quantifying Location Privacy. In 2011 IEEE Symposium on Security and Privacy (pp. 247–262). https://doi.org/10.1109/SP.2011.18Snekkenes, E. (2001). Concepts for Personal Location Privacy Policies. In Proceedings of the 3rd ACM Conference on Electronic Commerce (pp. 48–57). New York, NY, USA: ACM. https://doi.org/10.1145/501158.501164Tang, K. P., Lin, J., Hong, J. I., Siewiorek, D. P., & Sadeh, N. (2010). Rethinking location sharing: exploring the implications of social-driven vs. purpose-driven location sharing. In Proceedings of the 12th ACM international conference on Ubiquitous computing (pp. 85–94). ACM.
Details
| Primary Language | English |
|---|---|
| Subjects | Communication and Media Studies |
| Journal Section | Articles |
| Authors | |
| Publication Date | November 30, 2018 |
| Published in Issue | Year 2018 Volume: 1 Issue: 2 |