Analyzing user preferences using Facebook fan pages

Pin Luarn; Hsien Chih Kuo; Hong Wen Lin; Yu Ping Chiu; Ya Cing Jhan

doi:10.1287/inte.2017.0919

Analyzing user preferences using Facebook fan pages

Pin Luarn, Hsien Chih Kuo, Hong Wen Lin, Yu Ping Chiu, Ya Cing Jhan

Research output: Contribution to journal › Editorial › peer-review

4 Citations (Scopus)

Abstract

With the increasing numbers of Facebook fan-page users, finding information based on their interests has become di cult, and fan-page managers are challenged as they try to understand the needs of these users. To understand their needs and preferences and increase the e ectiveness of fan-page marketing, we use two-step clustering to group 42,953 Facebook fan-page users. The results of our study show seven clusters, each with di erent key characteristics. We label them as lurk, informational, health and beauty, visual lady, intellectual reader, consumption and shopping, and highly active fans. One of our objectives in this paper is to help fan-page managers use our results to target users and to draft management strategies.

Original language	English
Pages (from-to)	166-175
Number of pages	10
Journal	Interfaces
Volume	48
Issue number	2
DOIs	https://doi.org/10.1287/inte.2017.0919
Publication status	Published - 2018 Mar 1
Externally published	Yes

Keywords

Behavior
Information
Social network

ASJC Scopus subject areas

Strategy and Management
Management Science and Operations Research
Management of Technology and Innovation

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10.1287/inte.2017.0919

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title = "Analyzing user preferences using Facebook fan pages",

abstract = "With the increasing numbers of Facebook fan-page users, finding information based on their interests has become di cult, and fan-page managers are challenged as they try to understand the needs of these users. To understand their needs and preferences and increase the e ectiveness of fan-page marketing, we use two-step clustering to group 42,953 Facebook fan-page users. The results of our study show seven clusters, each with di erent key characteristics. We label them as lurk, informational, health and beauty, visual lady, intellectual reader, consumption and shopping, and highly active fans. One of our objectives in this paper is to help fan-page managers use our results to target users and to draft management strategies.",

keywords = "Behavior, Information, Social network",

author = "Pin Luarn and Kuo, {Hsien Chih} and Lin, {Hong Wen} and Chiu, {Yu Ping} and Jhan, {Ya Cing}",

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T1 - Analyzing user preferences using Facebook fan pages

AU - Luarn, Pin

AU - Kuo, Hsien Chih

AU - Lin, Hong Wen

AU - Chiu, Yu Ping

AU - Jhan, Ya Cing

PY - 2018/3/1

Y1 - 2018/3/1

N2 - With the increasing numbers of Facebook fan-page users, finding information based on their interests has become di cult, and fan-page managers are challenged as they try to understand the needs of these users. To understand their needs and preferences and increase the e ectiveness of fan-page marketing, we use two-step clustering to group 42,953 Facebook fan-page users. The results of our study show seven clusters, each with di erent key characteristics. We label them as lurk, informational, health and beauty, visual lady, intellectual reader, consumption and shopping, and highly active fans. One of our objectives in this paper is to help fan-page managers use our results to target users and to draft management strategies.

AB - With the increasing numbers of Facebook fan-page users, finding information based on their interests has become di cult, and fan-page managers are challenged as they try to understand the needs of these users. To understand their needs and preferences and increase the e ectiveness of fan-page marketing, we use two-step clustering to group 42,953 Facebook fan-page users. The results of our study show seven clusters, each with di erent key characteristics. We label them as lurk, informational, health and beauty, visual lady, intellectual reader, consumption and shopping, and highly active fans. One of our objectives in this paper is to help fan-page managers use our results to target users and to draft management strategies.

KW - Behavior

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KW - Social network

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VL - 48

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Analyzing user preferences using Facebook fan pages

Abstract

Keywords

ASJC Scopus subject areas

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