Usage
editThis is a template to create quote from research papers for the /Recent research column of The Signpost. It has four parameters.
|source=– The piece of research being highlighted. It supports {{cite xxx}} templates directly. For example
|source={{cite journal |last1=Lageard |first1=Valentin |last2=Paternotte |first2=Cédric |year=2018 |title='''Trolls, bans and reverts: Simulating Wikipedia''' |journal=Synthese |volume= |issue= |pages=1–20 |doi=10.1007/s11229-018-02029-0 }}
|note=– A small note, or commentary on the paper. For example
|note=See also the [http://wikigen.org/ WikiGen] website.
|quote=– A quote from the piece of research. Do not include quote marks.
|quote=The main threat to Wikipedia’s reliability, namely the presence of epistemically disruptive agents such as disinformers and trolls, turns out to be offset only by a combination of factors...
|from=– Where the quote comes from, exactly. By default, this is|from=the abstract.
|from=the back cover
Example
editOther recent publications
Other recent publications that could not be covered in time for this issue include the items listed below. Contributions, whether reviewing or summarizing newly published research, are always welcome.
Editing persistently is fun, but editing a lot is not
From the abstract.[1]
See also earlier coverage of a related paper by some of the same authors: "Emergent Role Behaviours in Wikipedia – The 'How' and 'Why'".... we explore challenges in compiling a pedagogic resource like a textbook on a given topic from relevant Wikipedia articles, and present an approach towards assisting humans in this task. We present an algorithm that attempts to suggest the textbook structure from Wikipedia based on a set of seed concepts (chapters) provided by the user. We also conceptualize a decision support system where users can interact with the proposed structure and the corresponding Wikipedia content to improve its pedagogic value. The proposed algorithm is implemented and evaluated against the outline of online textbooks on five different subjects. We also propose a measure to quantify the pedagogic value of the suggested textbook structure.
"Let's Talk About Refugees: Network Effects Drive Contributor Attention to Wikipedia Articles About Migration-Related Topics"
From the abstract.[2]
... we propose relational event models to analyze dynamic network effects explaining the allocation of contributor attention to Wikipedia articles about migration-related topics. Among others, we test for the presence of a rich-get-richer effect in which articles edited by many users are likely to receive even more contributions in the future and uncover which users start working on less popular articles. We further analyze local clustering effects in which pairs of users tend to repeatedly collaborate on the same articles ...
References
- ^ Balestra, Martina; Zalmanson, Lior; Cheshire, Coye; Arazy, Ofer; Nov, Oded (2017). "It was Fun, but Did it Last?". Proceedings of the ACM on Human-Computer Interaction. 1: 1–13. doi:10.1145/3134656.
Author's copy.
- ^ Lerner, Jürgen; Lomi, Alessandro (2019). "Let's Talk About Refugees: Network Effects Drive Contributor Attention to Wikipedia Articles About Migration-Related Topics" (PDF). In Luca Maria Aiello; Chantal Cherifi; Hocine Cherifi; Renaud Lambiotte; Pietro Lió; Luis M. Rocha (eds.). Complex Networks and Their Applications VII. Studies in Computational Intelligence. Springer International Publishing. pp. 211–222. ISBN 9783030054144.
