| Ralf Peters|
(Alternative names for this author)
|Co-authors||Kohler S., Thomas Wöhner, Wohner T.|
|Authorship||Publications (2), datasets (0), tools (0)|
|Citations||Total (3), average (1.5), median (1.5), max (3), min (0)|
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|Title||Keyword(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Automatic reputation assessment in Wikipedia||Reputation
User generated content
|International Conference on Information Systems 2011, ICIS 2011||English||2011||The online encyclopedia Wikipedia is predominantly created by anonymous or pseudonymous authors whose knowledge and motivations are unknown. For that reason there is an uncertainty in terms of their contribution quality. An approach to this problem is provided by automatic reputation systems, which have been becoming a new research branch in the recent years. In previous research, different metrics for automatic reputation assessment have been suggested. Nevertheless, the metrics are evaluated insufficiently and considered isolated only. As a result, the significance of these metrics is quite unclear. In this paper, we compare and assess seven metrics, both originated from the literature and new suggestions. Additionally, we combine these metrics via a discriminant analysis to deduce a significant reputation function. The analysis reveals that our newly suggested metric editing efficiency is particularly effective. We validate our reputation function by means of an analysis of Wikipedia user groups.||0||0|
|Assessing the quality of Wikipedia articles with lifecycle based metrics||WikiSym||English||2009||The main feature of the free online-encyclopedia Wikipedia is the wiki-tool, which allows viewers to edit the articles directly in the web browser. As a weakness of this openness for example the possibility of manipulation and vandalism cannot be ruled out, so that the quality of any given Wikipedia article is not guaranteed. Hence the automatic quality assessment has been becoming a high active research field. In this paper we offer new metrics for an efficient quality measurement. The metrics are based on the lifecycles of low and high quality articles, which refer to the changes of the persistent and transient contributions throughout the entire life span.||0||3|