Difference between revisions of "Online Reputation Systems"

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An online reputation system is a set of tools that combine collective feedback about users in order to share that information publicly.  This is done so that users can gain trust and get clues about the validity and reliability of other users.
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Online reputation systems do two things; they facilitate trustful interactions between strangers on the Internet, and they also ease the problems of information overload.
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== Trust ==
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Although not flawless, online reputation systems give "a reasonable indicator of a person's relative trustworthiness and reliability" <ref> Kwan 2009, p. 291.</ref>.  Online reputation systems are important because trust is more of a problem in online interactions than offline interactions.  In the online realm, normal cues usually used for trust, such as body language, tone of voice, and facial expression, are missing.  Trust in reputation systems let users know that other users have good intentions and that they are also capable of carrying out such intentions.
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== Information overload ==
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The second component to online reputation systems is easing information overload.  With all the information and feedback users can leave on the Internet, online reputation systems help consolidate and summarize the statistics.  This all-inclusive approach to reputation-building also ensures that all interactions are recorded and ideally, treated as important.
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== Issues and flaws ==
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Despite the fact that online reputation systems work fairly well, they do still present some issues, both in terms of trust and in terms of information overload.  First of all, online reputation systems are meaningless without user feedback.  Without participation from its users, there is no information for the systems to present. This can lead to another issue: building an initial reputation.  The first time a user joins an online setting that uses reputation systems, they are starting with a blank slate.  This can create difficulties for creating a reputation when there is no basis for other users to trust them.
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Another problem is that since new identities can usually be easily created, someone with a bad reputation can start over fresh without his full history attached. This can lead to deceitful, malicious behavior when other users' trust is exploited with this flaw.
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The ways in which online reputation systems deal with information overload are not perfect either.  Since most online reputation systems give an average score or total a number of responses, this lets individual cases sometimes slip by.  A summary of a user's statistics does not give all the information, nor does it necessarily give all the important information.
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In addition, these scoring systems can be manipulated into giving inaccurate portrayals of a user's online behavior history.
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== Types of systems ==
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There are many different types of systems, each with various advantages and disadvantages.  Some systems rate users on a numerical scale, others contain a collection of detailed responses, and others still can be a combination of those and other techniques.  Also response can be voluntary or non-voluntary, depending on the design of the system.
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Online reputation systems are used in many areas, including but not limited to
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*Electronic markets
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*News sharing websites
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*Recommender systems
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Online reputation systems have been thoroughly and scientifically analyzed in order to determine what makes a good online reputation system. 
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Ming Kwan and Deepak Ramachandra, members of technology thinktank nGenera Insight, suggested certain guidelines for creating such a system.  They suggest that a good system makes users accountable for their actions.  This gives them an incentive to behave well in an online setting. Another important feature of a good online reputation system is having a system where reputation is hard to achieve, making a good reputation more valuable.  Finally, they suggest providing tools for users to validate and authenticate other users so that trust may be established<ref>Kwan 2009, p. 309.</ref>.
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== Notes ==
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{{Reflist}}
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== References ==
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Kwan, M. (2009-01-01). Trust and Online Reputation Systems. Computing with social trust, 287-311.doi:10.1007/978-1-84800-356-9_11

Revision as of 04:24, 6 October 2011

An online reputation system is a set of tools that combine collective feedback about users in order to share that information publicly. This is done so that users can gain trust and get clues about the validity and reliability of other users.

Online reputation systems do two things; they facilitate trustful interactions between strangers on the Internet, and they also ease the problems of information overload.


Trust

Although not flawless, online reputation systems give "a reasonable indicator of a person's relative trustworthiness and reliability" [1]. Online reputation systems are important because trust is more of a problem in online interactions than offline interactions. In the online realm, normal cues usually used for trust, such as body language, tone of voice, and facial expression, are missing. Trust in reputation systems let users know that other users have good intentions and that they are also capable of carrying out such intentions.


Information overload

The second component to online reputation systems is easing information overload. With all the information and feedback users can leave on the Internet, online reputation systems help consolidate and summarize the statistics. This all-inclusive approach to reputation-building also ensures that all interactions are recorded and ideally, treated as important.


Issues and flaws

Despite the fact that online reputation systems work fairly well, they do still present some issues, both in terms of trust and in terms of information overload. First of all, online reputation systems are meaningless without user feedback. Without participation from its users, there is no information for the systems to present. This can lead to another issue: building an initial reputation. The first time a user joins an online setting that uses reputation systems, they are starting with a blank slate. This can create difficulties for creating a reputation when there is no basis for other users to trust them.

Another problem is that since new identities can usually be easily created, someone with a bad reputation can start over fresh without his full history attached. This can lead to deceitful, malicious behavior when other users' trust is exploited with this flaw.

The ways in which online reputation systems deal with information overload are not perfect either. Since most online reputation systems give an average score or total a number of responses, this lets individual cases sometimes slip by. A summary of a user's statistics does not give all the information, nor does it necessarily give all the important information.

In addition, these scoring systems can be manipulated into giving inaccurate portrayals of a user's online behavior history.


Types of systems

There are many different types of systems, each with various advantages and disadvantages. Some systems rate users on a numerical scale, others contain a collection of detailed responses, and others still can be a combination of those and other techniques. Also response can be voluntary or non-voluntary, depending on the design of the system.

Online reputation systems are used in many areas, including but not limited to

  • Electronic markets
  • News sharing websites
  • Recommender systems

Online reputation systems have been thoroughly and scientifically analyzed in order to determine what makes a good online reputation system. Ming Kwan and Deepak Ramachandra, members of technology thinktank nGenera Insight, suggested certain guidelines for creating such a system. They suggest that a good system makes users accountable for their actions. This gives them an incentive to behave well in an online setting. Another important feature of a good online reputation system is having a system where reputation is hard to achieve, making a good reputation more valuable. Finally, they suggest providing tools for users to validate and authenticate other users so that trust may be established[2].


Notes

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References

Kwan, M. (2009-01-01). Trust and Online Reputation Systems. Computing with social trust, 287-311.doi:10.1007/978-1-84800-356-9_11
  1. Kwan 2009, p. 291.
  2. Kwan 2009, p. 309.