Design of a system for the analysis
of social media content
Introduction
Methodology
Conclusion
References
• Boyd, D. M., Ellison, N. B. (2007). Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated
Communication, 13(1), p. 210-230.
• Pang, B.; Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends® in Information Retrieval. 2(2), p. 1-135.
• Ministr, J., Ráček, J. and Toth, D. (2012) ‘Visualization of the discussion content from the Internet’, IDIMT- 2012 ICT Support for
Complex Systems – 20th Interdisciplinary Information Management Talks, Jindřichův Hradec, Linz: Trauner Verlag, p. 297-304.
Jaroslav Ráček
Jaroslav.Racek@ibacz.eu
Faculty of Informatics, Masaryk University & IBA CZ
Brno, Czech Republic
Active users of social media produce large volumes
of data on a daily basis. This data could contain
patterns and expression of sentiments which have
value to commerce and academics alike.
Many algorithms and methods for analysing
social media data exist, but there is not any one
platform uniting these tools and services.
The solution is a design of a single system with four layers, to
integrate all required elements. These layers are the: collection
of data from different sources, data management and storage,
analytical algorithm usage focused on relevant aspects and
visualisation of analytical results and source data.
This paper introduces a design of new
component based system for social media
analysis, which can be easily configured for use in
academic and also commercial environment in
traditional areas of social media analysis. The
system was designed on the basis of applied
research in cooperation with industrial partners
of FI MU.
• Chronologically arranged posts vs. threads of
posts
• Expressions of opinions, attitudes and
reactions that can be viewed by other users.
• Indirect conversation with benefit of
hindsight
• Integration of all components in a single platform
• Provides human and software interface for visualisation of results
and access to retrieved data
• Specific configuration for different usage of the system
• Direct and indirect conversations, sharing of profile
content
• Mainly short messages, no general topic
• Long main article and related short comments
• General or focused on narrow area of interest
• Adapters for different data sources
• Different purposes: personal diary, significant
events of life, info about interests, company sites
• Interactive (commented) or static sites
• Specialized solutions for management of massive
amounts of data and running indexing on it
• Possibility of initial filtering of data
• Essential task for text analysis
• Identification of key terms contained in a source
text
• “Social” network of users, groups, similar
behaviour
• General part of any specific analytical tool
• Visualisation of analysis results in a form of
different types of graphs and record details
• Identification of multiple identities as the
same person
• Using behaviour patterns, timing of posts,
typos, phrases
• Evaluation of text combinations by comparison
to records in knowledge base
Dalibor Toth
xtoth2@fi.muni.cz
&