Return On Contribution (ROC): A Metric for Enterprise Social Software

Müller, Michael; Freyne, Jill; Dugan, Casey; Millen, David R.; Thom-Santelli, Jennifer

doi:10.1007/978-1-84882-854-4_8

Cited by 22 publications

(15 citation statements)

References 5 publications

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“…It should be noted that neither the textual content of the posts nor the network structure were exploited by our personalization model (Berkovsky and Freyne, 2015). The textual content of the posts was discarded primarily due to the fact that the majority of user activities in the Online TWD portal refer to content contribution rather than to content consumption, which is in line with trends observed on larger general-purpose SNs (Muller et al, 2009). The absence of network structure features is explained by the small scale and relative sparsity of the friendship graph, as the SN of the Online TWD portal differed from the usual familiarity-based SN.…”

Section: Conclusion and Discussionmentioning

confidence: 98%

Personalized Social Network Activity Feeds for Increased Interaction and Content Contribution

Berkovsky

Freyne

2015

Front. Robot. AI

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Citation:Berkovsky S and Freyne J (2015) Personalized social network activity feeds for increased interaction and content contribution. Front. Robot. AI 2:24. Online social networks were originally conceived as means of sharing information and activities with friends, and their success has been one of the primary contributors of the tremendous growth of the Web. Social network activity feeds were devised as a means to aggregate recent actions of friends into a convenient list. But the volume of actions and content generated by social network users is overwhelming, such that keeping users up-to-date with friend activities is an ongoing challenge for social network providers. Personalization has been proposed as a solution to combat social network information overload and help users to identify the nuggets of relevant information in the incoming flood of network activities. In this paper, we propose and thoroughly evaluate a personalized model for predicting the relevance of the activity feed items, which informs the ranking of the feeds and facilitates personalization. Results of a live study show that the proposed feed personalization approach successfully identifies and promotes relevant feed items and boosts the uptake of the feeds. In addition, it increases the contribution of user-generated content to the social network and spurs interaction between users.

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Section: Conclusion and Discussionmentioning

confidence: 98%

Personalized Social Network Activity Feeds for Increased Interaction and Content Contribution

Berkovsky

Freyne

2015

Front. Robot. AI

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“…Muller et al [25] assume that the use of a collaboration tooland also an ESS -is created strategically by forming the consumption and creation of information as collaborative processes. Therefore, they suggest a metric "Return on Creation" (ROC) to observe the usage patterns, thereby ignoring all other stakeholders of these systems.…”

Section: Related Workmentioning

confidence: 99%

Measuring success of enterprise social software

Lehner

Langbauer

Amende

2014

Proceedings of the 14th International Conference on Knowledge Technologies and Data-Driven Business

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With platforms like YouTube at hand, people from all over the world consume (unprofessionally produced) video tutorials to fix their individual problems. There can also be witnessed a certain willfulness to not only consume but contribute by creating and sharing own videos. In addition to the general availability of such public platforms and their content, companies realize the promising chances to (co-)manage comparable systems themselves to serve their specific purposes in day-to-day business communication, collaboration and information sharing. Therefore, high potential to contribute to the company`s well-fare can be assumed for diverse application scenarios and various industries, even gaining momentum by including modern forms of interactivity. Possible application scenarios reach from collaboratively solving a field service engineer's problem at hand through on-site video authoring to video-based instructions as innovative application in the field of e-health. Yet without evidence, the management is likely to discard the chances provided by so-called hypervideos in a practical context. So, in this conceptual work we show how hypervideo systems can be checked context-specifically for economic viability.

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“…This is a common method used for large-scale studies of social media usage within an organization [8,0,11,12,14,15,25,29,40]. For each community, we extracted • a list of owner and member IDs…”

Section: Shared Resourcesmentioning

confidence: 99%

“…We are studying several different algorithms for measuring interaction opportunities in social media (e.g., [29]); Relational Capital is our candidate metric for communities. For this paper, we will use a method based on combinatorics within a discussion thread (or equivalent structure).…”

Section: Relational Capitalmentioning

confidence: 99%

“…Our work can contribute precision regarding types of communities, which can be used in conjunction with broader models of Collaboration Personas [22] and other explorations of the organizational adoption of social media [10,11,14,16,34,38,43,45]. Stronger methods for classifying communities can clarify agendas for determining organizational benefits (e.g., [29]), and crucial attributes of successful communities.…”

Section: Implications For Theorymentioning

confidence: 99%

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Diversity among enterprise online communities

Müller

Ehrlich

Matthews

et al. 2012

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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There is a growing body of research into the adoption and use of social software in enterprises. However, less is known about how groups, such as communities, use and appropriate these technologies, and the implications for community structures. In a study of 188 very active online enterprise communities, we found systematic differences in size, demographics and participation, aligned with differences in community types. Different types of communities differed in their appropriation of social software tools to create and use shared resources, and build relationships. We propose implications for design of community support features, services for potential community members, and organizations looking to derive value from online groups.

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Return On Contribution (ROC): A Metric for Enterprise Social Software

Cited by 22 publications

References 5 publications

Personalized Social Network Activity Feeds for Increased Interaction and Content Contribution

Personalized Social Network Activity Feeds for Increased Interaction and Content Contribution

Measuring success of enterprise social software

Diversity among enterprise online communities

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