Inflation in Reputation Systems? Newcomers, Veterans, and Socialization within a Platform Community

Rating inflation is prevalent in reputation systems and can reduce their informational value. Through an exploratory mixed‐method study, we examine how and why rating inflation behavior evolves over time as reviewers socialize within an online reputation system platform community. We show that some reviewers are more prone to inflation while others avoid it. We draw on the theory of reciprocity and distinguish among three archetypical phases of reviewers: (1) the Newcomer Phase, (2) the Inflator Phase, and (3) the Veteran Phase. Newcomers who are not yet socialized in the platform community are less likely to inflate their ratings. Inflators exhibit the social norm of direct reviewer reciprocity and inflate their ratings. Veterans, reflecting the social norm of generalized reviewer reciprocity, are less likely to inflate ratings. Instead, they are more candid because they are driven by a commitment to help the platform community. These archetypical phases correspond to reviewers’ increasing socialization within the platform community and exposure to different digital platform affordances. Together, these processes shape which forms of reciprocity become salient over time—whether lacking, direct, or generalized—which consequently drive distinct reviewer behaviors. While most research on rating inflation emphasizes direct reciprocity, we highlight how reviewers can shift toward less inflated behaviors over time, aligning with generalized reciprocity towards the platform community. Thus, this exploratory work suggests an evolutionary process of rating behavior whereby rating inflation follows an inverted U-shape over the reviewer lifecycle.

Authors

Institutions

Publication Details

Journal
Information Systems Research
Published
2026-09-01
DOI
https://doi.org/10.1287/isre.2022.0321
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Inflation in Reputation Systems? Newcomers, Veterans, and Socialization within a Platform Community

Nicholas Berente, Yoonseock Son, John P. Lalor, Mareike Möhlmann
Information Systems Research
Digital Marketing and Social Media
article

Inflation in Reputation Systems? Newcomers, Veterans, and Socialization within a Platform Community

Nicholas Berente, Yoonseock Son, John P. Lalor, Mareike Möhlmann
article en

Abstract

Rating inflation is prevalent in reputation systems and can reduce their informational value. Through an exploratory mixed‐method study, we examine how and why rating inflation behavior evolves over time as reviewers socialize within an online reputation system platform community. We show that some reviewers are more prone to inflation while others avoid it. We draw on the theory of reciprocity and distinguish among three archetypical phases of reviewers: (1) the Newcomer Phase, (2) the Inflator Phase, and (3) the Veteran Phase. Newcomers who are not yet socialized in the platform community are less likely to inflate their ratings. Inflators exhibit the social norm of direct reviewer reciprocity and inflate their ratings. Veterans, reflecting the social norm of generalized reviewer reciprocity, are less likely to inflate ratings. Instead, they are more candid because they are driven by a commitment to help the platform community. These archetypical phases correspond to reviewers’ increasing socialization within the platform community and exposure to different digital platform affordances. Together, these processes shape which forms of reciprocity become salient over time—whether lacking, direct, or generalized—which consequently drive distinct reviewer behaviors. While most research on rating inflation emphasizes direct reciprocity, we highlight how reviewers can shift toward less inflated behaviors over time, aligning with generalized reciprocity towards the platform community. Thus, this exploratory work suggests an evolutionary process of rating behavior whereby rating inflation follows an inverted U-shape over the reviewer lifecycle.

Information Systems Research
University of Notre Dame (US), Bentley University (US)
Decent work and economic growth
Openalex Percentile: Top 5%
Digital Marketing and Social Media
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.