Reputation: A Network Interpretation

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Can I view this online? Ask a librarian. Bruce Walsh, Kenneth H. Craik, Ri Craik and Ervin H. Baird and Anthony D. Lutkus, editors ; foreword by Kenneth H.

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Aboriginal, Torres Strait Islander and other First Nations people are advised that this catalogue contains names, recordings and images of deceased people and other content that may be culturally sensitive. Book , Online - Google Books. Table of contents only Broken link? In a centralized world, we rely heavily on familiar brands that we trust to provide reputational information for services we have no previous direct interaction with. Reputation services like Yelp store ratings and provide the context necessary for interpreting reputational information. There are several reasons to create alternative centralized reputation services.

Centralized services have a biased incentive structure for interpreting reputation data and disproportionate power to modify it. For instance, movie ticket provider Fandango is incentivized to pump up movie ratings to sell more tickets and they can set ratings high to do so. This demonstrates how reputation data is subject to censorship, distortion, and deletion. Effectiveness of searching is diminished when data is closed to alternate interpretations for novel uses. Averaging ratings in this case removes information needed to discover bizarre cult films.

The amount of redundant, non-reusable work spent by users on rating things is astounding. Large quantities of user generated data is siloed, non-reinterpritable, and impermanent. This represents a significant loss of value to the users who created this content. A new era of peer to peer collaboration can be enabled through decentralized reputation services.

Reputation: A Network Interpretation - Kenneth H. Craik - Google книги

If executed well a scalable, decentralized, interoperable reputation network can make economic ecosystems considerably more productive. It is worth noting a few barriers to participation in growing reputation systems. Users fear durable negative reputation and this limits participation. Participants are also afraid of being categorized in unfair ways e. Fear of retribution for recording negative ratings limits contribution of potentially valuable data. Other adoption factors include cost of participation, availability of relevant data a network effect , and confidence in accuracy.

Permissionless access to decentralized systems serves several needs.


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For one, permissionless decentralized ledgers like Bitcoin grant access to electronic transactions for individuals that would not be able to acquire bank accounts due to lack of government identification, minimum bank balances, or poor credit scores. The low bar for account access enables progressive reputation accumulation. On these grounds, permissionless account access is a potential boon to those with untrustworthy banks, refugees, the homeless, and the poor.

Permissionless accounts also mean an increase in network size and network contributions. Advice from our personal networks reduces our search time for new products, services, ideas, and collaborators dramatically.

This benefit is magnified as we move from our in person network to online graphs. But these graphs are currently primarily provided by centralized services such as Google, Facebook, Twitter and the like. In a centralized world, we rely heavily on familiar brands that we trust to provide reputational information for services we have no previous direct interaction with.

Reputation: A Network Interpretation

Reputation services like Yelp store ratings and provide the context necessary for interpreting reputational information. There are several reasons to create alternative centralized reputation services. Centralized services have a biased incentive structure for interpreting reputation data and disproportionate power to modify it. For instance, movie ticket provider Fandango is incentivized to pump up movie ratings to sell more tickets and they can set ratings high to do so. This demonstrates how reputation data is subject to censorship, distortion, and deletion. Effectiveness of searching is diminished when data is closed to alternate interpretations for novel uses.

Averaging ratings in this case removes information needed to discover bizarre cult films. The amount of redundant, non-reusable work spent by users on rating things is astounding. Large quantities of user generated data is siloed, non-reinterpritable, and impermanent. This represents a significant loss of value to the users who created this content. A new era of peer to peer collaboration can be enabled through decentralized reputation services.

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If executed well a scalable, decentralized, interoperable reputation network can make economic ecosystems considerably more productive. It is worth noting a few barriers to participation in growing reputation systems. Users fear durable negative reputation and this limits participation. Participants are also afraid of being categorized in unfair ways e. Fear of retribution for recording negative ratings limits contribution of potentially valuable data. Other adoption factors include cost of participation, availability of relevant data a network effect , and confidence in accuracy.

Permissionless access to decentralized systems serves several needs. For one, permissionless decentralized ledgers like Bitcoin grant access to electronic transactions for individuals that would not be able to acquire bank accounts due to lack of government identification, minimum bank balances, or poor credit scores.

Reputation: A Network Interpretation

The low bar for account access enables progressive reputation accumulation. On these grounds, permissionless account access is a potential boon to those with untrustworthy banks, refugees, the homeless, and the poor. Permissionless accounts also mean an increase in network size and network contributions. Kaliya Hamlin Identity Woman defines the spectrum of identity like this:.

The exposure of reputation, account, and transaction data progressively remove anonymity and create a reputation profile. Virtual anonymity is decreased as information is progressively associated with a unique identity. Because of these factors it is important to investigate the interaction between reputation and the progressive loss of anonymity. Attribution: the synthesis of ideas here is heavily influenced by the insights of Harlan Wood and Matt Schutte. In order to preserve the utility of reputation information for multiple purposes, it must be available in its raw form.

The availability of this raw data enables many interpretations, using diverse algorithms, fit for specific decision making purposes. In a decentralized network the aggregation of reputation may be queried across many data storage sources. This data will likely be assembled by crawlers that provide standard data and standard algorithms for interpretation. Confidence in decentralized reputation data may be provided by cross referencing multiple reputation aggregation providers.

This interpretation may include both public and private data sources.