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Analysis of Facebook content demand patterns

Kihl, Maria LU ; Larsson, Robin LU ; Unnervik, Niclas; Haberkamm, Jolina; Arvidsson, Åke and Aurelius, Andreas (2014) International Conference on Smart Communications in Network Technologies (SaCoNeT) In [Host publication title missing]
Abstract
Data volumes in communication networks increase rapidly. Further, usage of social network applications is very wide spread among users, and among these applications, Facebook is the most popular. In this paper, we analyse user demands patterns and content popularity of Facebook generated traffic. The data comes from residential users in two metropolitan access networks in Sweden, and we analyse more than 17 million images downloaded by almost 16,000 Facebook users. We show that the distributions of image popularity and user activity may be described by Zipf distributions which is favourable for many types of caching. We also show that Facebook activity is more evenly spread over the day, compared to more defined peak hours of general... (More)
Data volumes in communication networks increase rapidly. Further, usage of social network applications is very wide spread among users, and among these applications, Facebook is the most popular. In this paper, we analyse user demands patterns and content popularity of Facebook generated traffic. The data comes from residential users in two metropolitan access networks in Sweden, and we analyse more than 17 million images downloaded by almost 16,000 Facebook users. We show that the distributions of image popularity and user activity may be described by Zipf distributions which is favourable for many types of caching. We also show that Facebook activity is more evenly spread over the day, compared to more defined peak hours of general Internet usage. Looking at content life time, we show that profile pictures have a relatively constant popularity while for other images there is an initial, short peak of demand, followed by a longer period of significantly lower and quite stable demand. These findings are useful for designing network and QoE optimisation solutions, such as predictive pre-fetching, proxy caching and delay tolerant networking. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
[Host publication title missing]
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
International Conference on Smart Communications in Network Technologies (SaCoNeT)
external identifiers
  • WOS:000345738400001
  • Scopus:84906311237
DOI
10.1109/SaCoNeT.2014.6867760
project
LCCC
EIT_NOTTS Next generation over-the-top multimedia services
EIT_EFRAIM Eco system for future media distribution
language
English
LU publication?
yes
id
4deae8bc-31d4-4289-97d0-943deaafb592 (old id 4812793)
date added to LUP
2014-11-25 14:00:40
date last changed
2016-10-13 04:37:10
@misc{4deae8bc-31d4-4289-97d0-943deaafb592,
  abstract     = {Data volumes in communication networks increase rapidly. Further, usage of social network applications is very wide spread among users, and among these applications, Facebook is the most popular. In this paper, we analyse user demands patterns and content popularity of Facebook generated traffic. The data comes from residential users in two metropolitan access networks in Sweden, and we analyse more than 17 million images downloaded by almost 16,000 Facebook users. We show that the distributions of image popularity and user activity may be described by Zipf distributions which is favourable for many types of caching. We also show that Facebook activity is more evenly spread over the day, compared to more defined peak hours of general Internet usage. Looking at content life time, we show that profile pictures have a relatively constant popularity while for other images there is an initial, short peak of demand, followed by a longer period of significantly lower and quite stable demand. These findings are useful for designing network and QoE optimisation solutions, such as predictive pre-fetching, proxy caching and delay tolerant networking.},
  author       = {Kihl, Maria and Larsson, Robin and Unnervik, Niclas and Haberkamm, Jolina and Arvidsson, Åke and Aurelius, Andreas},
  language     = {eng},
  publisher    = {ARRAY(0x90d9a18)},
  series       = {[Host publication title missing]},
  title        = {Analysis of Facebook content demand patterns},
  url          = {http://dx.doi.org/10.1109/SaCoNeT.2014.6867760},
  year         = {2014},
}