Lukasz Porwol

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A proliferation of e-participation research in recent years has produced fragmented contributions in the area of e-participation models. Without a mechanism for analyzing, relating and consolidating these models, further development of the domain is in danger of repeating itself. This paper presents such a mechanism -- an Integrative Framework which(More)
What remains unclear after a decade of e-Participation research and practice is the extent to which the social web and informal channels have empowered citizens in government-citizen interactions where government determines what, where and how to discuss. Lately, attention has shifted to how these informal channels could be better harnessed as part of a(More)
There have been limited efforts so far to mainstream social media-based citizen-led political deliberations and its integration with traditional government-led e-Participation. Thus, while notion of duality of e-Participation is plausible -- the mutual (re-)shaping of the deliberations on traditional e-Participation and social media; significant(More)
There have been limited efforts so far to provide a detailed conceptualization and formal ontology for e-Participation. Current e-Participation literature is replete with fragmented models, which only partially describe aspects of e-Participation. Consequently consistent descriptions and comparison of e-Participation initiatives is difficult. In addition,(More)
The increasing volumes of datasets published on open data platforms have had little impact on the public use of open data and perceived transparency of respective governments. At the same time, the innovation potentials of these datasets are far from realized due to many factors including poor quality of datasets. While past studies have attempted to(More)
Recent efforts to mainstream social media-based and citizen-led political deliberations to complement traditional government-led e-Participation, must among others address a number of technical challenges. One of these challenges is how to automatically filter and extract meaningful information or knowledge from streams of social media data contributed by(More)