The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index; none of the 9 sources its claims cite is checked for support yet.
Reputation systems
Open accessAbstract
T he Internet offers vast new opportunities to interact with total strangers. These interactions can be fun, informative, even profitable. But they also involve risk. Is the advice of a self-proclaimed expert at expertcentral.com reliable? Will an unknown dotcom site or eBay seller ship items promptly with appropriate packaging? Will the product be the same one described online?
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
30 Own interpretation · 10 No basis given · 5 Sources not found · 2 No full text of the sources
In the paper
“Nevertheless, the overall rate of successful transactions remains astonishingly high for a market as”
- Also stated in: § MARC MONGEAU · hedged
“ripe with the possibility of largescale fraud and deceit”
What the sources say
- Not checked — no full text of the sourcecites [5] 5. Kollock, P. The production of trust in online markets. In Advances in Group Processes, vol. 16, E. Lawler, M. Macy, S. Thyne, and H. Walker, Eds. JAI Press, Greenwich, CT, 1999; see also www.sscnet.ucla.edu/soc/f aculty/kollock/papers/online_trust.htm.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § MARC MONGEAU · hedged
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The first is that people may not bother to provide feedback at all.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Such premiums are observed in auctions in auctions of coins and computer chips on eBay [3,6,7].”
What the sources say
- Not matchedcites [3] 3. Bajari, P. and Hortacsu, A. Winner's curse, reserve prices, and endogenous entry: Empirical insights from eBay auctions; see www.stanford.edu/ ~bajari/wp/auction/ebay.pdf.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [6] 6. Lucking-Reiley, D., Bryan, D., Prasad, N., and Reeves, D. Pennies from eBay: The determinants of price in online auctions; see www.vanderbilt.edu/econ/reiley/papers/PenniesFromEBay.pdf.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [7] 7. Houser, D. and Wooders, J. Reputation in auctions: Theory and evidence from eBay; see bpa.arizona.edu/~jwooders/ebay.pdf.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Third is the difficulty of ensuring honest reports.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“these systems help people decide whom to trust, encourage trustworthy behavior, and deter participation by those who are unskilled or dishonest.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“these systems help people decide whom to trust, encourage trustworthy behavior, and deter participation by those who are unskilled or dishonest.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Reputation systems seek to establish the shadow of the future to each transaction by creating an expectation that other people will look back on it.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Game-theory analysis demonstrates that there are inherent limitations to the effectiveness of reputation systems when participants are allowed to start over with new names [4].”
What the sources say
- Not matchedcites [4] 4. Friedman, E. and Resnick, P. The social cost of cheap pseudonyms; see www.si.umich.edu/~presnick/papers/identifiers/index.html.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A second difficulty in distributing feedback stems from the lack of portability from system to system.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Second, the expectation of reciprocity or retaliation in future interactions creates an incentive for good behavior.”
What the sources say
- Not matchedcites [2] 2. Axelrod, R. The Evolution of Cooperation. Basic Books, New York, 1984.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
- Probably not a substantial claim. 20
- It may state two separate claims as one. 10
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Despite their theoretical and practical difficulties, it is reassuring that reputation systems appear to perform reasonably well.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: eBay's high rate of successful transactions is attributable to its reputation system.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“At eBay, for example, a stream of buyers interacts with the same seller.They may never buy an item from the seller again, but by sharing their opinions about the seller via the Feedback Forum, they construct a meaningful history of the seller.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If buyers do behave this way, the sellers' reputations will affect their future sales.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Despite this promise, significant challenges remain in the operating phases of such systems: eliciting, distributing, and aggregating feedback.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“Over time, high-quality sellers would desert the market.Eventually, only the lowest-quality sellers would remain, a dynamic economist George Akerlof memorialized as the”
- Also stated in: § MARC MONGEAU · plain
“market for lemons”
What the sources say
- Not checked — no full text of the sourcecites [1] 1. Akerlof, G. The market for 'lemons': Quality uncertainty and the market mechanism. Quart. J. Econom. 84 (1970), 488-500. source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § MARC MONGEAU · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Even then, fear of retaliatory negative feedback or simply a desire to avoid further unpleasant interactions may keep a dissatisfied buyer quiet.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Systems that rely on the participation of large numbers of individuals accumulate trust simply by operating effectively over time.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, sellers with stellar reputations may enjoy a premium on their services; some users may be willing to pay for the security and comfort of high-quality services.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In terms of building trust, a boost in the quantity of information compensates for a significant reduction in its quality.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“In particular, newcomers (those with no feedback) should always be distrusted until they have somehow paid their dues, either through an entry fee or by accepting more risk or worse prices while developing their reputations.”
What the sources say
- Not matchedcites [4] 4. Friedman, E. and Resnick, P. The social cost of cheap pseudonyms; see www.si.umich.edu/~presnick/papers/identifiers/index.html.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These simple numerical ratings fail to convey important subtleties of online interactions; for example, Did the feedback come from low-value transactions?What were the reputations of the people providing the feedback?”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Internet services operate on a vastly larger scale”
- Also stated in: § MARC MONGEAU · plain
“than Main Street and permit virtually anonymous interactions.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
- Also stated in: § MARC MONGEAU · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“• Long-lived entities that inspire an expectation of future interaction;”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Today's reputation systems, by contrast, shouldn't work in theory.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“• Use of feedback to guide trust decisions.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“With clear reputation markers, low-quality sellers get lower prices, leaving a healthier market with a variety of prices and quality of service.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Prior to the Internet, such questions were answered, in part, through personal and corporate reputations.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Strangers lack known past histories or the prospect of future interaction, and they are not subject to a network of informed individuals who would punish bad and reward good behavior.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“These interactions can be fun, informative, even profitable.But they also involve risk.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“• Capture and distribution of feedback about current interactions (such information must be visible in the future); and”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The Internet can vastly accelerate and add structure to the process of capturing and distributing information.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“One party could blackmail another, threatening to post negative feedback unrelated to actual performance.At the other extreme, in order to accumulate positive feedback, a group of sellers might collaborate and rate one another positively, artificially inflating their individual reputations.”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Future buyers, lacking personal histories with particular sellers, may still base their buying decisions on a sufficiently extensive public history.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When agreeing to be rated is optional (such as when registering as a retailer at bizrate.com), doing so is likely an indication of higher-quality services, even before ratings are available.”
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Even if all reporting were complete and honest, users would find it virtually impossible to utilize the torrents of information they receive on other participants, given the lack of satisfactory summary statistics.”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Limited distribution of feedback limits its effectiveness; the future casts a shadow on only a single online arena, not on many.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The authors state this as an assumption.
Buyers provide and rely on feedback in reputation systems.
“provide and rely on feedback-isolated interactions take on attributes of long-term relationships.”
The paper relies on this without support.
eBay's high rate of successful transactions is attributable to its reputation system.
“The high rate of successful transactions is attributerd by eBay to its reputation system, called the Feedback Forum.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Resnick et al. (2000) stated that the lack of reputation portability is problematic as ''[l]imited distribution of feedback limits its effectiveness'' (p. 48).”
From In Stars We Trust – A Note on Reputation Portability Between Digital Platforms (2022) · cites this paper as Resnick et al. 2000
The cited source says what the claim attributes to it.
In the citing paper
“The growth of e-auctions and other forms of e-commerce is based, to a considerable degree, on reputation and trust 5-10 .”
From Evolution of indirect reciprocity (2005) · cites this paper as [9]
In the citing paper
“Past research has argued that reputation systems and user-generated reviews may have the primary purpose of allowing users to learn more about each other before engaging in any interactions or transactions, acting as a monitoring and policing system [5,66,67].”
From Digital Identity: The effect of trust and reputation information on user judgement in the Sharing Economy (2018) · cites this paper as [67]
Citations
Cites
The Market for "Lemons": Quality Uncertainty and the Market Mechanism
Akerlof, G. A. (1970) · The Quarterly Journal of Economics · doi:10.2307/1879431 · Cited by 23,016
Axelrod, R., & Hamilton, W. D. (1981) · Science · doi:10.1126/science.7466396 · Cited by 20,065
Nielsen, R. P., & Axelrod, R. (1985) · Academy of Management Review · doi:10.2307/257983 · Cited by 6,517
The Winner's Curse, Reserve Prices, and Endogenous Entry: Empirical Insights from eBay Auctions
Bajari, P., Hortaçsu, A., & Hortacsu, A. (2003) · The RAND Journal of Economics · doi:10.2307/1593721 · Cited by 1,041
PENNIES FROM EBAY: THE DETERMINANTS OF PRICE IN ONLINE AUCTIONS*
Lucking‐Reiley, D., Bryan, D., Prasad, N., & Reeves, D. M. (2007) · Journal of Industrial Economics · doi:10.1111/j.1467-6451.2007.00309.x · Cited by 550
(1999) · Advances in group processes · Cited by 426
Lawler, E. J., & Thye, S. R. (2000) · Advances in group processes · doi:10.1016/s0882-6145(2000)17 · Cited by 247
How not to build an online market: the sociology of market microstructure
Kollock, P., & Braziel, E. R. (n.d.) · Advances in Group Processes · doi:10.1016/s0882-6145(06)23011-x
Cited by
Sorted by citations
Items 901–1,000 of 2,164
Dellarocas, C. N. (2004) · Chapman & Hall/CRC computer and information science series · doi:10.1201/9780203507223.ch20 · Cited by 13
Raghunath, A., Ndubuisi-Obi, I., Mpogole, H., & Anderson, R. (2023) · ACM Journal on Computing and Sustainable Societies · doi:10.1145/3616386 · Cited by 12
“Reputation systems designed to be sybil-proof and publicly verifiable could serve as deterrents to agent malfeasance [54, 55].”
BackgroundLi, S., Li, J., Liang, Y., et al. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3347870 · Cited by 12
“Using reputation [17], [18] as a metric for trustworthiness, determined based on past behaviours, enables TD-SAS to prioritize vehicles with higher reputation values.”
Bounded-Confidence Models of Opinion Dynamics with Adaptive Confidence Bounds
Li, G. J., Luo, J., & Porter, M. A. (2025) · SIAM Journal on Applied Dynamical Systems · doi:10.1137/23m1558951 · Cited by 15
Collective Ratings for Online Communities With Strategic Users
Zhang, Y., & van der Schaar, M. (2014) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2014.2320457 · Cited by 10
“V. IMPACT OF THE GROUP SIZE Different from the existing personal rating protocols (e.g. [21], [22]), the size of a group (i.e. the number of workers managed by a group operator) plays an important role in the design of collective rating protocols, which determines the incentive of individual…”
BackgroundFighting pollution attacks in P2P streaming
Tauhiduzzaman, M., & Wang, M. (2015) · Computer Networks · doi:10.1016/j.comnet.2014.12.009 · Cited by 12
A Survey of Quality Prediction of Product Reviews
Almagrabi, H., Malibari, A., & McNaught, J. (2015) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2015.061107 · Cited by 12
“Some trust metrics from other studies may be of use to determine the helpfulness of product reviews, for example, research into peer-to-peer and reputation networks [64, 65, 66, 67, 68].”
BackgroundLeverage a Trust Service Platform for Data Usage Control in Smart City
Truong, N. B., Cao, Q. H., Um, T., et al. (2016) · Globecom · doi:10.1109/glocom.2016.7841951 · Cited by 12
“The first method uses mathematical models such as weighted sum, Bayesian neutron networks [16], heuristic algorithms [17] or Google PageRank-like algorithms [9] for computing some sorts of TMs and TAs such as Recommendation and Reputation.”
MethodTrust Model for Cloud Based on Cloud Characteristics
Pawar, P. S., Rajarajan, M., Dimitrakos, T., et al. (2013) · IFIP advances in information and communication technology · doi:10.1007/978-3-642-38323-6_18 · Cited by 12
“The use of trust in the field of computer science is observed in diverse areas such as e-commerce, peer-to-peer, multi-agent systems, security and access control in computer networks, reliability in distributed networks, game theory and agent systems and policies for making decision under uncertainty [8][11][12].”
BackgroundAutomatic Reputation Assessment in Wikipedia
Wöhner, T., Köhler, S., & Peters, R. (2011) · International Conference on Information Systems · Cited by 12
Product reputation model : an opinion mining basedapproach
Abdel‐Hafez, A., Xu, Y., & Tjondronegoro, D. (2012) · QUT ePrints (Queensland University of Technology) · Cited by 12
A Reputation Multi-agent System in Semantic Web
Wang, W., Zeng, G., & Yuan, L. (2006) · Lecture notes in computer science · doi:10.1007/11802372_22 · Cited by 12
Countering feedback sparsity and manipulation in reputation systems
Xiong, L., Liu, L., & Ahamad, M. (2007) · International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom) · doi:10.1109/colcom.2007.4553831 · Cited by 12
“By harnessing the community knowledge in the form of feedback, they help participants decide who (what) to trust, encourage trustworthy behavior, and deter dishonest participation [27].”
BackgroundRecommender Services in Scientific Digital Libraries
Franke, M., Geyer-Schulz, A., & Neumann, A. (2008) · Studies in computational intelligence · doi:10.1007/978-3-540-78502-6_15 · Cited by 12
“For reputation services, similar mechanism design problems exists as for recommender services [57].”
BackgroundWhy Users Disintermediate Peer-to-Peer Marketplaces
Bellotti, V. M. E., Turner, D., Demkova, K., Ambard, A., & Waterman, A. (2017) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025815 · Cited by 14
“P2PMs compensate for lack of trust between strangers with reputation systems [38, 50] but, although such systems may offer many benefits, as far as trust goes, they have no advantage over OOM transactions, because OOM transactions happen after participants have been introduced by the P2PM and…”
BackgroundLemoine, L. E., Guesmi, S., & Hadhri, W. (2017) · Question(s) de management · doi:10.3917/qdm.174.0077 · Cited by 12
Liu, W., Feng, X., Zhang, F., et al. (2018) · IEEE Access · doi:10.1109/access.2018.2838765 · Cited by 12
“[26], [27] used B2B as the research subject, conducted a qualitative study on the risk in the credit mechanism, proposed a new concept of ‘‘trust’’, introduced the impact of this concept in the operation of the e-commerce environment, and emphasized that improving integrity can reduce risk and transaction costs.”
MethodARM: Toward Adaptive and Robust Model for Reputation Aggregation
Zhou, X., Murakami, Y., Ishida, T., Liu, X., & Huang, G. (2019) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2019.2902407 · Cited by 12
“Since Resnick et al. [1] pointed out the issues dogging the reputation model in e-commerce platforms, many reputation systems have been published intending to accurately capture the reputation of services.”
BackgroundElmurngi, E. I., & Gherbi, A. (2019) · International Journal of Organizational and Collective Intelligence · doi:10.4018/ijoci.2020010103 · Cited by 13
Uncheatable Reputation for Distributed Computation Markets
Cărbunar, B., & Sion, R. (2006) · Lecture notes in computer science · doi:10.1007/11889663_7 · Cited by 12
Designing On-Line Mediation Services for C2C Markets
Zhao, X., Fang, F., & Whinston, A. B. (2006) · International Journal of Electronic Commerce · doi:10.2753/jec1086-4415100303 · Cited by 12
A novel penalty model for managing and applying penalties in Cloud Computing
Maarouf, A., Qacimy, B. E., Marzouk, A., et al. (2015) · doi:10.1109/aiccsa.2015.7507243 · Cited by 12
“Another kind of penalty clause can lead to a change in the reputation of a provider [9] [10].”
BackgroundFaderank: An Incremental Algorithm for Ranking Twitter Users
Bartoletti, M., Lande, S., & Massa, A. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-48743-4_5 · Cited by 12
“The underlying assumption is that, by analysing the past interaction history of an object, one can predict the quality of its future interactions [10,22].”
BackgroundA Trust Scheme Based on Vehicles Reports of Events in VANETs
Wan, J., Gu, X., Wang, J., et al. (2018) · Wireless Personal Communications · doi:10.1007/s11277-018-6106-6 · Cited by 12
Trust Enhanced Security - A New Philosophy for Secure Collaboration of Mobile Agents
Lin, C., & Varadharajan, V. (2006) · International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom) · doi:10.1109/colcom.2006.361905 · Cited by 12
A Connection-Centric Survey of Recommender Systems ResearchPreprint
Perugini, S., Gonçalves, M. A., & Fox, E. A. (2002) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0205059 · Cited by 12
What’s in a Username? Identity Cue Effects in Social Media
Taylor, S. J., Muchnik, L., & Aral, S. (2014) · doi:10.2139/ssrn.2538130 · Cited by 10
A Stochastic Approach for Trust Management
Haller, J. (2006) · doi:10.1109/icdew.2006.20 · Cited by 12
Dark Side of Online Social Networks: Technical, Managerial, and Behavioral Perspectives
Kéfi, H., & Pérez, C. (2017) · Springer eBooks · doi:10.1007/978-1-4614-7163-9_110217-1 · Cited by 13
UbiBay: An auction system for mobile multihop ad-hoc networks
Frey, H., & Lehnert, J. K. (2004) · Cited by 12
The Influence of Social Media Marketing on Voting Intention in Indonesia
Moslehpour, M., Schafferer, C., Lewi, S., Kurniawati, D., Pham, V. K., & Faez, S. (2024) · Journal of Political Marketing · doi:10.1080/15377857.2024.2303509 · Cited by 10
“Because of these voids, recommendations are an integral part of any deliberation procedure (Kleinberg and Raghavan 2005; Resnick et al. 2000; Bakos and Dellarocas 2011; Dash, Ramchurn, and Jennings 2004).”
AdContRep: A Privacy Enhanced Reputation System for MANET Content Services
Yan, Z., & Chen, Y. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-16355-5_33 · Cited by 11
“eBay [14], Yahoo auctions [18], and Internet-based systems such as Keynote [24]).”
BackgroundC-trust: A trust management system to improve fairness on circular P2P networks
Naghizadeh, A., Razeghi, B., Meamari, E., et al. (2015) · Peer-to-Peer Networking and Applications · doi:10.1007/s12083-015-0402-7 · Cited by 11
Personalized video recommendation based on viewing history with the study on YouTube
Zhao, X., Luan, H., Cai, J., et al. (2012) · International Conference on Internet Multimedia Computing and Service · doi:10.1145/2382336.2382382 · Cited by 11
“beyond user’s ability to evaluate even a small fraction of them; and (2) users do not have the initiative to rate the viewed videos [19].”
BackgroundReputation Systems: Evaluating Reputation Among All Good Sellers
Jha, V., Ramu, S., Shenoy, P. D., & Venugopal, K. R. (2017) · Data-Enabled Discovery and Applications · doi:10.1007/s41688-017-0008-8 · Cited by 11
The value of reputation in electronic marketplaces
Yang, Y., Sun, X., & Wang, J. (2019) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-11-2018-0151 · Cited by 13
A Characterisation of Consumer Empowerment Drawn from Three Views of Power
Alshibly, H. H., Aisbett, J., & Pires, G. D. (2014) · Developments in marketing science: proceedings of the Academy of Marketing Science · doi:10.1007/978-3-319-11761-4_99 · Cited by 11
“Luhmann (1979) notes that in the commercial sphere, trust is built upon information that reflects a seller’s reputation, policies, practices and performance history, In customer loyalty theory, building trust leads to longer-term relationships and higher longterm profits (although the high cost of acquiring customers…”
BackgroundThe economics of professional services: lemon markets, credence goods, and C2C information sharing
d’Andria, D. (2012) · Service Business · doi:10.1007/s11628-012-0143-0 · Cited by 11
The Impact of Testimonials on Purchase Intentions in a Mock E-commerce Web Site
Spillinger, A., & Parush, A. (2012) · Journal of theoretical and applied electronic commerce research · doi:10.4067/s0718-18762012000100005 · Cited by 11
“Instead of basing trust on a previous personal interaction, in which the other party (the seller) acted as expected [27], it can be assumed that trust develops through the experiences of other consumers who are members in the community.”
BackgroundRL-based routing in biomedical mobile wireless sensor networks using trust and reputation
Naputta, Y., & Usaha, W. (2012) · International Symposium on Wireless Communication Systems · doi:10.1109/iswcs.2012.6328422 · Cited by 11
“E-commerce systems, such as ebay (Resnick and Zeckhauser 2000), Yahoo auctions (Resnick et al. 2000).”
BackgroundFeature Extraction for Fraud Detection in Electronic Marketplaces
Maranzato, R. P., Neubert, M., Pereira, A. C. M., & do Lago, A. P. (2009) · Latin American Web Congress · doi:10.1109/la-web.2009.20 · Cited by 11
“[24] say that these reputation systems have”
BackgroundMethodInfluentialDISARM: A social distributed agent reputation model based on defeasible logic
Kravari, K., & Bassiliades, N. (2016) · Journal of Systems and Software · doi:10.1016/j.jss.2016.02.016 · Cited by 11
“models help agents to decide who to trust, encouraging trustworthy behavior and deterring dishonest participation by providing the mean through which reputation and ultimately trust can be quantified [43]. Hence, as intelligent agents are gradually enriched with Semantic Web technology [18, 6, 5], acting on behalf of…”
BackgroundPrivacy-Preserving User Data Oriented Services for Groups with Dynamic Participation
Kononchuk, D., Erkin, Z., van der Lubbe, J. C. A., & Lagendijk, R. L. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40203-6_24 · Cited by 10
TRR: An integrated Reliability-Reputation Model for Agent Societies
Rosaci, D., Sarnè, G. M. L., & Garruzzo, S. (2011) · Cited by 11
A unified knowledge compiler to provide support the scientific community
Fernández-Isabel, A., Prieto, J. C., Ortega, F., de Diego, I. M., Moguerza, J. M., Mena, J., Galindo, S., & Napalkova, L. (2018) · Knowledge-Based Systems · doi:10.1016/j.knosys.2018.07.044 · Cited by 11
Przepiorka, W., & Aksoy, O. (2020) · Social Forces · doi:10.1093/sf/soaa057 · Cited by 11
“In online markets, traders provide feedback about their trading partners’ conduct after finished transactions, and this information is collected, aggregated, and made immediately available to everyone online (Kollock 1999; Resnick et al. 2000; Dellarocas 2003).”
BackgroundIntermediation in reward-based crowdfunding: a cash deposit mechanism to reduce moral hazard
Erjiang, E., Yu, M. Y., & Peng, G. (2021) · Electronic Commerce Research · doi:10.1007/s10660-021-09462-3 · Cited by 11
From Reputation Models and Systems to Reputation Ontologies
Alnemr, R., & Meinel, C. (2011) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/978-3-642-22200-9_10 · Cited by 11
“Resnick [29] defines a reputation system as: ”a system that collects, distributes, and aggregates feedback about participants’ past behavior” .”
Measuring the Importance of Users in a Social Network Based on Email Communication Patterns
Lubarski, P., & Morzy, M. (2012) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1109/asonam.2012.24 · Cited by 11
“For a quick introduction we refer the reader to [13], [15] and [14].”
Multimedia information retrieval and environmental monitoring: Shared perspectives on data fusion
Smeaton, A. F., O’Connor, E., & Regan, F. B. (2013) · Ecological Informatics · doi:10.1016/j.ecoinf.2013.10.004 · Cited by 11
A vector based model approach for defining trust in Multi-Organization Environments
Toumi, K., Andrés, C. G., Cavalli, A. R., et al. (2012) · International Conference on Risks and Security of Internet and Systems (CRiSIS) · doi:10.1109/crisis.2012.6378939 · Cited by 11
“According to [17], the evaluation of the reputation of an entity must respect some properties.”
BackgroundMulti-layer Monitoring for Cloud Computing
́lez, J. G., Muñoz, A., & Maña, A. (2011) · IEEE International Symposium on High Assurance Systems Engineering (HASE) · doi:10.1109/hase.2011.65 · Cited by 11
“[6-9])), trust is currently poorly assessed for the purposes of the dynamic deployment of software.”
BackgroundA reputation system for electronic negotiations
Tafreschi, O. A., Mähler, D., Fengel, J., Rebstock, M., & Eckert, C. M. (2008) · Computer Standards & Interfaces · doi:10.1016/j.csi.2008.03.003 · Cited by 11
“A reputation system collects, distributes and aggregates feedback about participants’ past behavior [15].”
BackgroundStudying the ethical implications of e-trust in the lab
Bicchieri, C., & Lev‐On, A. (2010) · Ethics and Information Technology · doi:10.1007/s10676-010-9258-y · Cited by 11
“Resnick et al. (2000) argue that the way feedback and ratings are displayed in such systems can have tremendous impact over the exchange decisions of participants, as they focus the attention on certain aspects of the potential partners that may have been otherwise overlooked.”
BackgroundOperational Models for Reputation Servers
Chadwick, D. W. (2005) · Lecture notes in computer science · doi:10.1007/11429760_8 · Cited by 11
“: iTrust 2005, LNCS 3477, pp. 108 – 115, 2005.”
A Bi-rating Based Personalized Trust Management Model for Virtual Communities
Meng, K., Zhang, X., Xiao, X., et al. (2006) · IEEE International Conference on Networking, Sensing and Control (ICNSC) · doi:10.1109/icnsc.2006.1673154 · Cited by 11
Tags and image scoring for robust cooperation
Griffiths, N. (2008) · Warwick Research Archive Portal (University of Warwick) · doi:10.5555/1402298.1402305 · Cited by 11
The HMM-based model for evaluating recommender's reputation
Song, W., Phoha, V. V., & Xu, X. (2005) · IEEE International Conference on E-Commerce Technology for Dynamic E-Business · doi:10.1109/cec-east.2004.64 · Cited by 11
“Evaluation of recommenders' reputations is important in Ecommerce and P2P networks [7][9].”
BackgroundDecentralized Privacy Preserving Reputation System
Owiyo, E., Wang, Y., Asamoah, E., Kamenyi, D., & Obiri, I. A. (2018) · IEEE International Conference on Data Science in Cyberspace · doi:10.1109/dsc.2018.00106 · Cited by 11
Leveraging Product Characteristics for Online Collusive Detection in Big Data Transactions
Luo, S., & Wan, S. (2019) · IEEE Access · doi:10.1109/access.2019.2891907 · Cited by 11
“A study which compared the fraudsters selling the same products with different reputations score was carried out on eBay [58].”
BackgroundThwarting P2P Pollution Using Object Reputation
Walsh, K. S., & Sirer, E. G. (2005) · Cited by 11
Incentive mechanism for the CoopNet network
Manzato, D. A. G., & da Fonseca, N. L. S. (2008) · Peer-to-Peer Networking and Applications · doi:10.1007/s12083-007-0004-0 · Cited by 11
A Privacy-Aware Identity Design for Exploring Ubiquitous Collaborative Wisdom
Hwang, Y., & Yuan, S.-T. D. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-72590-9_59 · Cited by 11
Computer Supported Activity Coordination
Cordeiro, J. A. (2004) · Cited by 11
Recommendation and Personalization: A SurveyPreprint
Perugini, S., & Andr, M. (2002) · arXiv (Cornell University) · Cited by 12
A Survey on Reputation and Trust-Based Systems for Wireless Communication NetworksPreprint
Sen, J. (2010) · arXiv (Cornell University) · doi:10.48550/arxiv.1012.2529 · Cited by 11
Searching for reputable source code on the web
Gallardo-Valencia, R. E., Tantikul, P., & Sim, S. E. (2010) · doi:10.1145/1880071.1880102 · Cited by 11
Decentralized security mechanisms for routing protocols
Katz, R. H., Stoica, I. G., & Subramanian, L. (2005) · Cited by 11
Bolton, G. E., & Chen, Y. (2018) · doi:10.1002/9781119138341.ch6 · Cited by 11
Trust and information privacy concerns in electronic government
Beldad, A. D. (2011) · doi:10.3990/1.9789036531689 · Cited by 9
Lock-In Effects in Online Labor MarketsPreprint
Ciotti, F., Hornuf, L., & Stenzhorn, E. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3953015 · Cited by 11
Trust, reputation, and the value of promises in online auctions of used goods
Kas, J., Corten, R., & van de Rijt, A. (2023) · Rationality and Society · doi:10.1177/10434631231170342 · Cited by 10
A rating aggregation method for generating product reputations
Abdel‐Hafez, A., Xu, Y., & Jøsang, A. (2014) · ACM Conference on Hypertext and Social Media (HT) · doi:10.1145/2631775.2631779 · Cited by 10
“Therefore, reputation systems are an essential part of any e-commerce or product reviews websites, where they provide methods for collecting and aggregating users’ ratings in order to calculate the overall reputation scores for products, users, or services [1].”
BackgroundAgreeing on Role Adoption in Open Organisations
Aldewereld, H., Dignum, V., Jonker, C. M., et al. (2011) · Künstliche Intell. · doi:10.1007/s13218-011-0152-5 · Cited by 10
“See, for example, [17,21,24].”
FLOW-BASED REPUTATION: MORE THAN JUST RANKING
Simone, A., Škorić, B., & Zannone, N. (2012) · International Journal of Information Technology & Decision Making · doi:10.1142/s0219622012500113 · Cited by 10
“Reputation systems are widely considered as ‘the solution’ to assess trust relationships among users and to identify and isolate malicious users [28].”
BackgroundInteractive Reputation Systems
Sänger, J., & Pernul, G. (2017) · Business & Information Systems Engineering · doi:10.1007/s12599-017-0493-1 · Cited by 10
“They then collect all feedback created, aggregate the ratings to compute one or several reputation values and present the output in a feedback profile (Resnick et al. 2000).”
BackgroundCellina, F., Derboni, M., Giuffrida, V., Tomić, U., & Hoerler, R. (2024) · Travel Behaviour and Society · doi:10.1016/j.tbs.2024.100832 · Cited by 10
Cluster-Based Analysis and Recommendation of Sellers in Online Auctions
Morzy, M., & Jezierski, J. (2006) · Lecture notes in computer science · doi:10.1007/11824633_18 · Cited by 10
“One of the mechanisms to build trust between anonymous participants of online auctions are reputation systems [11].”
BackgroundEffective Usage of Computational Trust Models in Rational Environments
Vu, L., & Aberer, K. (2011) · ACM Transactions on Autonomous and Adaptive Systems · doi:10.1145/2019591.2019593 · Cited by 10
“The traditional way to enforce the cooperation of a provider via a reputation mechanism is to allow a client to rate the service of the provider as good or bad after finishing the transaction [Resnick et al. 2000].”
BackgroundAljazzaf, Z. M. (2011) · Scholarship@Western (Western University) · Cited by 9
Sänger, J., Hänsch, N., Glass, B. D., Benenson, Z., Landwirth, R., & Sasse, M. A. (2016) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858555 · Cited by 9
“For this reason, reputation systems [48] have become popular tools.”
BackgroundIn Pursuit of Personalization Design
Kaneko, K., Kishita, Y., & Umeda, Y. (2017) · Procedia CIRP · doi:10.1016/j.procir.2016.12.003 · Cited by 10
Yamashita, J., Seto, T., Nishimura, Y., et al. (2019) · International Journal of Cartography · doi:10.1080/23729333.2019.1613086 · Cited by 10
“, 2018) and reputation (Resnick et al., 2000) affect VGI data quality.”
BackgroundUser-Centered Design in Pediatric Acute Care Settings Antimicrobial Stewardship
Ward, M. J., Chavis, B., Banerjee, R., Katz, S. E., & Anders, S. H. (2021) · Applied Clinical Informatics · doi:10.1055/s-0040-1718757 · Cited by 9
Using Reputation Scores to Foster Car-Sharing Activities
Postorino, M. N., & Sarnè, G. M. L. (2023) · Sustainability · doi:10.3390/su15043295 · Cited by 10
Personalizing Trust in Online Auctions
O’Donovan, J., Evrim, V., Smyth, B., et al. (2006) · eCite Digital Repository (University of Tasmania) · Cited by 10
Design and Analysis of a Game Theoretic Model for P2P Trust Management
Harish, M., Anandavelu, N., Anbalagan, N., et al. (2007) · Springer eBooks · doi:10.1007/978-3-540-77115-9_11 · Cited by 10
Dynamical Trust and Reputation Computation Model for B2C E-Commerce
Tian, B., Liu, K., & Chen, Y. (2015) · Future Internet · doi:10.3390/fi7040405 · Cited by 11
Expert Competition and the Internet
Akçura, M. T., Özdemir, Z. D., & Jain, S. (2013) · International Journal of Electronic Commerce · doi:10.2753/jec1086-4415180101 · Cited by 10
A guide to trust in mobile ad hoc networks
Balfe, S., Yau, P., & Paterson, K. G. (2009) · Security and Communication Networks · doi:10.1002/sec.147 · Cited by 10
“The use of reputation systems in many different areas of information technology is increasing, not least because of their widely publicised use in online auctions and product reviews, see, for example, eBay and Amazon [65].”
BackgroundPantola, A. V., Pancho-Festin, S., & Salvador, F. (2010) · International Conference on Security of Information and Networks (SIN) · doi:10.1145/1854099.1854116 · Cited by 10
“In eBay, for example, buyers and sellers have the opportunity to provide feedback by rating each other after a transaction is completed [23, 24].”
BackgroundThe Design and Evaluation of a Peer Ratings System for Online Learning Communities
Thoms, B., Garrett, N., & Ryan, T. (2010) · Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · doi:10.1109/hicss.2010.370 · Cited by 10
Dynamic trust assessment of software services
Spanoudakis, G. (2007) · doi:10.1145/1294928.1294937 · Cited by 10
“Other work focuses on the effect of national culture on consumer trust [23][22], website credibility [18] and reputation [33][12].”
BackgroundResearch on Trust Propagation Models in Reputation Management Systems
Su, Z., Li, M., Fan, X., et al. (2014) · Mathematical Problems in Engineering · doi:10.1155/2014/536717 · Cited by 10
“Trust computing, the core part of reputation management system, also has a wide range of applications in eCommerce, mobile computing, peer to peer computing, sensor computing, and social computing, to name a few [1–3].”
BackgroundLiu, Y., Zhou, W., & Chen, H. (2017) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2017.2668992 · Cited by 10
“The colluding malicious users can (1) provide high ratings for self-promoting; (2) provide low ratings for bad-mouthing [8]–[10]; (3) restore their reputation by providing honest ratings to products that they do not care [35], [36]; or (4) whitewash their reputation by registering new user IDs [37].”
BackgroundOutline Reputation Scores: How Well are They Understood?
Gregg, D. G. (2009) · Journal of Computer Information Systems · doi:10.1080/08874417.2009.11645366 · Cited by 10
“These online reputation systems collect, distribute, and aggregate feedback about online respondents’ past behaviour [37].”
Cooperation with Bottom-up Reputation Dynamics
Xu, J., García, J. A., & Handfield, T. (2019) · Adaptive Agents and Multi-Agents Systems · doi:10.65109/zruj5916 · Cited by 12
Producer Anonymity Based on Onion Routing in Named Data Networking
Kita, K., Koizumi, Y., Hasegawa, T., Ascigil, O., & Psaras, I. (2020) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2020.3019052 · Cited by 10
“Therefore, if necessary, trust should be established to producers’ onion names instead of their identities by using reputation systems or in some ad-hoc manners [25], [26], [27].”
BackgroundOckenfels, A., & Resnick, P. (2012) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199730858.013.0016 · Cited by 12
Self-citation
Metadata
- Authors
- Resnick, P., Kuwabara, K., Zeckhauser, R., & Friedman, E.
- Affiliations
- University of Michigan (US)
- Harvard University (US)
- Rutgers, The State University of New Jersey (US)
- Venue
- Communications of the ACM
- Published
- 2000-12
- Volume
- 43
- Issue
- 12
- Pages
- 45-48
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2337430557
- Cited by
- 2,190
- References
- 7
- Citations by year
- 2026: 38 · 2025: 32 · 2024: 37 · 2023: 33 · 2022: 36 · 2021: 52 · 2020: 58 · 2019: 66 · 2018: 66 · 2017: 87 · 2016: 87 · 2015: 93 · 2014: 110 · 2013: 111 · 2012: 134
- FWCI
- 145.25
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Communications of the ACM (publishedVersion)
- Funders
- National Science Foundation (9977999)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Access Control and Trust
- Physical Sciences › Computer Science › Information Systems › Expert finding and Q&A systems
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- reputation systems, online trust, online interaction, e-commerce, peer reputation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-11, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-11 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
