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When E-Commerce Personalization Systems Show and Tell: Investigating the Relative Persuasive Appeal of Content-Based versus Collaborative Filtering
Mengqi Liao,
S. Shyam Sundar
Film-Video and Media Studies
Research output
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Contribution to journal
›
Comment/debate
›
peer-review
47
Scopus citations
Overview
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Dive into the research topics of 'When E-Commerce Personalization Systems Show and Tell: Investigating the Relative Persuasive Appeal of Content-Based versus Collaborative Filtering'. Together they form a unique fingerprint.
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Business & Economics
Bandwagon Effect
34%
Collaborative Filtering
100%
Electronic Commerce
54%
Endorsements
27%
Evaluation
12%
Experiment
13%
Heuristics
36%
Need for Cognition
31%
Personalization
77%
Product Category
45%
Recommender Systems
30%
Social Psychology
26%
Strategic Communication
30%
Transparency
24%
User Preferences
29%
Social Sciences
appeal
56%
artificial intelligence
13%
bandwagon effect
22%
cognition
11%
commerce
69%
communications
11%
electronic business
31%
evaluation
6%
experiment
8%
heuristics
25%
personalization
76%
social psychology
13%
transparency
11%
Engineering & Materials Science
Artificial intelligence
20%
Collaborative filtering
78%
Communication
11%
Consumer products
29%
Electronic commerce
79%
Experiments
8%
Recommender systems
23%
Transparency
23%