Convex Games Versus Clan Games

Brânzei, R.; Dimitrov, Dinko; Tijs, S.H.

doi:10.1142/s0219198908001996

Cited by 4 publications

(4 citation statements)

References 14 publications

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“…As we saw in the previous section, the worker dynamics and—to a certain extent—the task and algorithm designers’ choices can impact the behavior and performance of the self-organized worker collective. In the future, it would be useful to examine this through the lens of cooperative game theory (Chalkiadakis et al, 2012; Branzei et al, 2008). Using this approach, mathematical models of strategic agents representing the online workers can be constructed, and a variety of scenarios can be simulated examining the effects of their interactions and collective tendencies in detail.…”

Section: Resultsmentioning

confidence: 99%

Self-organization in online collaborative work settings

Lykourentzou

Vinella

Ahmed

et al. 2022

Collective Intelligence

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As the volume and complexity of distributed online work increases, collaboration among people who have never worked together in the past is becoming increasingly necessary. Recent research has proposed algorithms to maximize the performance of online collaborations by grouping workers in a top-down fashion and according to a set of predefined decision criteria. This approach often means that workers have little say in the collaboration formation process. Depriving users of control over whom they will work with can stifle creativity and initiative-taking, increase psychological discomfort, and, overall, result in less-than-optimal collaboration results—especially when the task concerned is open-ended, creative, and complex. In this work, we propose an alternative model, called Self-Organizing Pairs (SOPs), which relies on the crowd of online workers themselves to organize into effective work dyads. Supported but not guided by an algorithm, SOPs are a new human-centered computational structure, which enables participants to control, correct, and guide the output of their collaboration as a collective. Experimental results, comparing SOPs to two benchmarks that do not allow user agency, and on an iterative task of fictional story writing, reveal that participants in the SOPs condition produce creative outcomes of higher quality, and report higher satisfaction with their collaboration. Finally, we find that similarly to machine learning-based self-organization, human SOPs exhibit emergent collective properties, including the presence of an objective function and the tendency to form more distinct clusters of compatible collaborators.

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Section: Resultsmentioning

confidence: 99%

Self-organization in online collaborative work settings

Lykourentzou

Vinella

Ahmed

et al. 2022

Collective Intelligence

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“…While game theory, and in particular leader-follower game, has already been employed in the context of allocation of divisible resources [ 98 ], the application of such techniques to community-based peer production is novel. Future research directions for game theory in this area include the use of cooperative game theory [ 99 ] to study the stability of the production process; applying coalitional game models [ 100 ] to analyze how competing coalitions of contributors emerge, applying resilience and immunity models [ 101 ] to investigate how the peer production process performs in cases of deviations from expected behavior, and using evolutionary game theory [ 102 ] to study how unexpected behaviors emerge as a result of sequential actions by different contributors. Game theory can also be used to develop models that would account for the relationship between individual’s governance work and the community’s overall governance level while using algorithm and mechanism design [ 103 ] to determine the most effective community governance structures.…”

Section: Discussionmentioning

confidence: 99%

A game-theoretic analysis of Wikipedia’s peer production: The interplay between community’s governance and contributors’ interactions

et al. 2023

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Peer production, such as the collaborative authoring of Wikipedia articles, involves both cooperation and competition between contributors. Cooperatively, Wikipedia’s contributors attempt to create high-quality articles, and at the same time, they compete to align Wikipedia articles with their personal perspectives and “take ownership” of the article. This process is governed collectively by the community, which works to ensure the neutrality of the content. We study the interplay between individuals’ cooperation and competition, considering the community’s endeavor to ensure a neutral point of view (NPOV) on articles. We develop a two-level game-theoretic model: the first level models the interactions between individual contributors who seek both cooperative and competitive goals and the second level models governance of co-production as a Stackelberg (leader-follower) game between contributors and the communal neutrality-enforcing mechanisms. We present our model’s predictions regarding the relationship between contributors’ personal benefits of content ownership and their characteristics, namely their cooperative/competitive orientation and their activity profile (whether creators or curators of content). We validate the model’s prediction through an empirical analysis, by studying the interactions of 219,811 distinct contributors that co-produced 864 Wikipedia articles over a decade. The analysis and empirical results suggest that the factor that determines who ends up owning content is the ratio between one’s cooperative/competitive orientation (estimated based on whether a core or peripheral community member) and the contributor’s creator/curator activity profile (proxied through average edit size per sentence). Namely, under the governance mechanisms, the fractional content that is eventually owned by a contributor is higher for curators that have a competitive orientation. Although neutrality-seeking mechanisms are essential for ensuring that ownership is not concentrated within a small number of contributors, our findings suggest that the burden of excessive governance may deter contributors from participating, and thus indirectly curtail the peer production of high-quality articles.

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“…One aspect of analyzing such a game is to quantify, for each player , the value of the player with respect to the game (see, e.g., Branzei et al. 2008 for a more detailed exposition of these concepts).…”

Section: The Shapely Valuementioning

confidence: 99%

Phylogenetic Diversity Indices from an Affine and Projective Viewpoint

Moulton,

Spillner,

Wicke

2024

Bull Math Biol

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Phylogenetic diversity indices are commonly used to rank the elements in a collection of species or populations for conservation purposes. The derivation of these indices is typically based on some quantitative description of the evolutionary history of the species in question, which is often given in terms of a phylogenetic tree. Both rooted and unrooted phylogenetic trees can be employed, and there are close connections between the indices that are derived in these two different ways. In this paper, we introduce more general phylogenetic diversity indices that can be derived from collections of subsets (clusters) and collections of bipartitions (splits) of the given set of species. Such indices could be useful, for example, in case there is some uncertainty in the topology of the tree being used to derive a phylogenetic diversity index. As well as characterizing some of the indices that we introduce in terms of their special properties, we provide a link between cluster-based and split-based phylogenetic diversity indices that uses a discrete analogue of the classical link between affine and projective geometry. This provides a unified framework for many of the various phylogenetic diversity indices used in the literature based on rooted and unrooted phylogenetic trees, generalizations and new proofs for previous results concerning tree-based indices, and a way to define some new phylogenetic diversity indices that naturally arise as affine or projective variants of each other or as generalizations of tree-based indices.

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Convex Games Versus Clan Games

Cited by 4 publications

References 14 publications

Self-organization in online collaborative work settings

Self-organization in online collaborative work settings

A game-theoretic analysis of Wikipedia’s peer production: The interplay between community’s governance and contributors’ interactions

Phylogenetic Diversity Indices from an Affine and Projective Viewpoint

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