Knowledge discovery in web traffic log: A case study of facebook usage in Kasetsart University

Chakkrit Tantithamthavorn; Arnon Rungsawang

doi:10.1109/JCSSE.2012.6261960

Knowledge discovery in web traffic log: A case study of facebook usage in Kasetsart University

Chakkrit Tantithamthavorn, Arnon Rungsawang

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

1 Citation (Scopus)

Abstract

Recognizing and understanding knowledge flow between user interactions in social networks are valuable for sociology, economy, political science, and marketing. In this paper, we present a methodology in order to extract information and discover knowledge from a web traffic log. Our study is based on traffic and login history logs of Kasetsart University's network during a 7-days period from March 1-7, 2011. The summarized HTTP sessions show 39,046 distinct users together with 25,894 IP addresses. We conduct a pattern analysis in six aspects: The Origin of HTTP Requests, Distribution of HTTP Requests at the level of hostname, Time spent communicating online, Overall Traffic Workload Analysis, Facebook Traffic Workload Analysis and Web Access Patterns. The results reveal many interesting patterns and knowledge from raw data.

Original language	English
Title of host publication	JCSSE 2012 - 9th International Joint Conference on Computer Science and Software Engineering
Pages	247-252
Number of pages	6
DOIs	https://doi.org/10.1109/JCSSE.2012.6261960
Publication status	Published - 24 Sept 2012
Externally published	Yes
Event	2012 9th International Joint Conference on Computer Science and Software Engineering, JCSSE 2012 - Bangkok, Thailand Duration: 30 May 2012 → 1 Jun 2012

Conference

Conference	2012 9th International Joint Conference on Computer Science and Software Engineering, JCSSE 2012
Country/Territory	Thailand
City	Bangkok
Period	30/05/12 → 1/06/12

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10.1109/JCSSE.2012.6261960

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@inproceedings{14915a74857f46e2affff44075bdea95,

title = "Knowledge discovery in web traffic log: A case study of facebook usage in Kasetsart University",

abstract = "Recognizing and understanding knowledge flow between user interactions in social networks are valuable for sociology, economy, political science, and marketing. In this paper, we present a methodology in order to extract information and discover knowledge from a web traffic log. Our study is based on traffic and login history logs of Kasetsart University's network during a 7-days period from March 1-7, 2011. The summarized HTTP sessions show 39,046 distinct users together with 25,894 IP addresses. We conduct a pattern analysis in six aspects: The Origin of HTTP Requests, Distribution of HTTP Requests at the level of hostname, Time spent communicating online, Overall Traffic Workload Analysis, Facebook Traffic Workload Analysis and Web Access Patterns. The results reveal many interesting patterns and knowledge from raw data.",

author = "Chakkrit Tantithamthavorn and Arnon Rungsawang",

year = "2012",

month = sep,

day = "24",

doi = "10.1109/JCSSE.2012.6261960",

language = "English",

isbn = "9781467319218",

pages = "247--252",

booktitle = "JCSSE 2012 - 9th International Joint Conference on Computer Science and Software Engineering",

note = "2012 9th International Joint Conference on Computer Science and Software Engineering, JCSSE 2012 ; Conference date: 30-05-2012 Through 01-06-2012",

}

Tantithamthavorn, C & Rungsawang, A 2012, Knowledge discovery in web traffic log: A case study of facebook usage in Kasetsart University. in JCSSE 2012 - 9th International Joint Conference on Computer Science and Software Engineering., 6261960, pp. 247-252, 2012 9th International Joint Conference on Computer Science and Software Engineering, JCSSE 2012, Bangkok, Thailand, 30/05/12. https://doi.org/10.1109/JCSSE.2012.6261960

Knowledge discovery in web traffic log: A case study of facebook usage in Kasetsart University. / Tantithamthavorn, Chakkrit; Rungsawang, Arnon.
JCSSE 2012 - 9th International Joint Conference on Computer Science and Software Engineering. 2012. p. 247-252 6261960.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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Y1 - 2012/9/24

N2 - Recognizing and understanding knowledge flow between user interactions in social networks are valuable for sociology, economy, political science, and marketing. In this paper, we present a methodology in order to extract information and discover knowledge from a web traffic log. Our study is based on traffic and login history logs of Kasetsart University's network during a 7-days period from March 1-7, 2011. The summarized HTTP sessions show 39,046 distinct users together with 25,894 IP addresses. We conduct a pattern analysis in six aspects: The Origin of HTTP Requests, Distribution of HTTP Requests at the level of hostname, Time spent communicating online, Overall Traffic Workload Analysis, Facebook Traffic Workload Analysis and Web Access Patterns. The results reveal many interesting patterns and knowledge from raw data.

AB - Recognizing and understanding knowledge flow between user interactions in social networks are valuable for sociology, economy, political science, and marketing. In this paper, we present a methodology in order to extract information and discover knowledge from a web traffic log. Our study is based on traffic and login history logs of Kasetsart University's network during a 7-days period from March 1-7, 2011. The summarized HTTP sessions show 39,046 distinct users together with 25,894 IP addresses. We conduct a pattern analysis in six aspects: The Origin of HTTP Requests, Distribution of HTTP Requests at the level of hostname, Time spent communicating online, Overall Traffic Workload Analysis, Facebook Traffic Workload Analysis and Web Access Patterns. The results reveal many interesting patterns and knowledge from raw data.

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Y2 - 30 May 2012 through 1 June 2012

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Knowledge discovery in web traffic log: A case study of facebook usage in Kasetsart University

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