Understanding Development and Usage of Social Networking Sites: The Social Software Performance Model

Dwyer, Catherine; Hiltz, Starr Roxanne; Widmeyer, George R.

doi:10.1109/hicss.2008.476

Cited by 44 publications

(22 citation statements)

References 27 publications

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“…While developed in the 1990s to explain patterns of use in group support systems (GSS), AST has recently been applied to analyses of social software [13,14,18,28]. While this paper specifically focuses on measures of appropriation, a more detailed description of AST and its application to the study of SNS can be found in [14,18].…”

Section: The Importance Of Reliable Measures For Social Computingmentioning

confidence: 99%

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Developing Reliable Measures of Privacy Management within Social Networking Sites

Dwyer

Hiltz

Poole

et al. 2010

2010 43rd Hawaii International Conference on System Sciences

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Besides providing a benefit for future study of SNS, reliable, valid measures are urgently needed due to the unprecedented scale of participation in these sites. SNS have memberships that number in the tens of millions, drawing from countries around the globe [7].It can be argued SNS are the largest examples of information systems that have ever existed. Some information systems theories, such as the Technology Acceptance Model, have been applied to social computing applications [40], but these efforts show that considerable modification needs to be carried out to traditional information systems theory to yield reliable results. So while information systems theory holds much promise in the analysis of social computing, the differences between systems developed for a commercial enterprise versus one for the general population require a reconsideration and re-validation of both theory and related measures. Given the complexity of social computing, most measures must be focused on particular tools and affordances of the SNS rather than the SNS as a whole.In this study we focus on privacy management tools and the nature of their use.

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Section: The Importance Of Reliable Measures For Social Computingmentioning

confidence: 99%

“…Few if any measures for items regarding the use of these sites were available, and so these had to be developed and validated. More detailed descriptions of prior studies can be found in [15][16][17][18].…”

Section: Empirical Tests Of Privacy Management Scalesmentioning

confidence: 99%

Developing Reliable Measures of Privacy Management within Social Networking Sites

Dwyer

Hiltz

Poole

et al. 2010

2010 43rd Hawaii International Conference on System Sciences

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“…A definition provided by boyd and Ellison (boyd & Ellison, 2008) outlines three main features that define SNSs and will be used for the purposes of this research. SNSs are "web-based services that allow individuals to (1) construct a public or semi-public profile within a bounded system, (2) articulate a list of other users with whom they share a connection, and (3) (Dwyer, Hiltz, & Widmeyer, 2008).…”

Section: Defining Snss and Its Usementioning

confidence: 99%

Publishing personal information online

2016

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Purpose – The purpose of this paper is to examine employers’ use of social networking sites (SNSs) within employee selection. Design/methodology/approach – In-depth interviews were conducted with 15 organisations to gain an understanding of how they accessed, observed and utilised data from SNSs in their selection procedures, as well as gaining an insight into employers’ perceptions of candidate privacy and discrimination. Findings – SNS profiles were either accessed as part of an organisation’s official selection process, through integrating internet screening as part of the formal process and obtaining candidate permission, or through covert (without consent) observation. Facebook was primarily used to identify a candidate’s organisation fit and make assessment of their soft skills, whereas LinkedIn distinguished their professional attributes and their job fit. Problems were associated with the extent to which SNSs were reflective of the person and whether a candidate’s personal life reflected their work persona. Respondents focused more upon the legality, rather than the ethics, of accessing “private” information via SNSs. Research limitations/implications – Further research is needed to consider the content and predictive validity of SNSs as a selection tool before their utility can be ascertained. Practical implications – Organisations should have a clear goal when utilising SNSs, be aware of the value of the information and consider how it complements other selection tools. Selectors should have integrity throughout the selection process, view SNSs as a support tool and use their common sense. Originality/value – The in-depth nature of this research enabled the authors to understand how and why organisations are currently utilising SNSs within selection.

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“…Academic research related to SNS focuses on many different facets, including (but not limited to) user behavior (e.g., Bolar, 2009;Ellison, Steinfield, & Lampe, 2007), privacy and trust (e.g., Acquisti & Gross, 2006;Dwyer, Hiltz, & Widmeyer, 2008) and the unique properties of social networks (e.g., Boyd & Ellison, 2008;Richter & Koch, 2008). Recently, studies that are devoted to modeling the textual content generated by SNS users have emerged.…”

Section: Overviewmentioning

confidence: 99%

The Dual Micro/Macro Informing Role of Social Network Sites: Can Twitter Macro Messages Help Predict Stock Prices?

2012

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This study proposes a framework for understanding the role of Social Network Sites (SNS) in informing clients at individual message (micro) and aggregate (macro) levels. To validate the micro/macro informer framework, we examine if an aggregate of Twitter messages can be used as a predictor of future stock prices of publicly traded companies. Our field study analyzes Twitter posts related to 18 Fortune500 companies using Latent Semantic Analysis to extract the semantic and conceptual content in the form of key themes. Using the factors comprising the themes, we fit a regression model that uses tweet volume and tweet topic strength to predict 8.3% of variability in stock prices beyond what is explained by the fluctuations of the stock market. Our results suggest that Twitter can be viewed as a macro informer for stock markets. This confirms our conjecture that SNS are both platforms for micro informing and macro informers. Our study should stimulate informing science researchers to examine other cases of macro informing and the role of data mining and text mining technologies in message aggregation for macro informing.

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Understanding Development and Usage of Social Networking Sites: The Social Software Performance Model

Cited by 44 publications

References 27 publications

Developing Reliable Measures of Privacy Management within Social Networking Sites

Developing Reliable Measures of Privacy Management within Social Networking Sites

Publishing personal information online

The Dual Micro/Macro Informing Role of Social Network Sites: Can Twitter Macro Messages Help Predict Stock Prices?

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