The Visualizer for Real-Time Analysis of Internet Trends
The current web has become a modern encyclopedia,
where people share their thoughts and ideas on various topics around
them. This kind of encyclopedia is very useful for other people who
are looking for answers to their questions. However, with the
growing popularity of social networking and blogging and ever
expanding network services, there has also been a growing diversity
of technologies along with a different structure of individual web
sites. It is therefore difficult to directly find a relevant answer for a
common Internet user. This paper presents a web application for the
real-time end-to-end analysis of selected Internet trends where the
trend can be whatever the people post online. The application
integrates fully configurable tools for data collection and analysis
using selected webometric algorithms, and for its chronological
visualization to user. It can be assumed that the application facilitates
the users to evaluate the quality of various products that are
mentioned online.
[1] J. Ginsberg, M. H. Mohebbi, R. S. Patel, L. Brammer, M. S. Smolinski
and L. Brilliant, “Detecting influenza epidemics using search engine
query data”. Nature, vol. 457(7232), pp. 1012-1014, 2009. doi:
10.1038/nature07634
[2] H. Choi and H. Varian, “Predicting the Present with Google Trends”.
Economic Record, vol. 88, no. 2–9, 2012. doi: 10.1111/j.1475-
4932.2012.00809.x
[3] S. Reilly, S. Richey, J. B. Taylor, “Using Google Search Data for State
Politics Research”. State Politics & Policy Quarterly, vol. 12(2), pp. 146-
159, 2012. doi: 10.1177/1532440012438889
[4] R. Malinský and I. Jelínek, “Trend Analysis Framework”. Proceedings
of the 14th International Conference WWW/INTERNET. IADIS Press,
vol. 14, pp. 161-166, 2015. ISBN: 978-989-8533-44-9.
[5] M. Keith and M. Schincariol, “Pro JPA 2”. Apress Media LLC, New
York, USA, 2013. ISBN: 978-1-4302-1956-9.
[6] Z. Wadia, H. Saleh, A. L. Christensen, “Pro JSF and HTML5: Building
Rich Internet Components”. Apress Media LLC, New York, USA, 2013.
ISBN: 978-1-4302-5010-4.
[7] PrimeTek Informatics, “PrimeFaces”. 2015 (online). Available:
http://primefaces.org. (30 November 2015).
[1] J. Ginsberg, M. H. Mohebbi, R. S. Patel, L. Brammer, M. S. Smolinski
and L. Brilliant, “Detecting influenza epidemics using search engine
query data”. Nature, vol. 457(7232), pp. 1012-1014, 2009. doi:
10.1038/nature07634
[2] H. Choi and H. Varian, “Predicting the Present with Google Trends”.
Economic Record, vol. 88, no. 2–9, 2012. doi: 10.1111/j.1475-
4932.2012.00809.x
[3] S. Reilly, S. Richey, J. B. Taylor, “Using Google Search Data for State
Politics Research”. State Politics & Policy Quarterly, vol. 12(2), pp. 146-
159, 2012. doi: 10.1177/1532440012438889
[4] R. Malinský and I. Jelínek, “Trend Analysis Framework”. Proceedings
of the 14th International Conference WWW/INTERNET. IADIS Press,
vol. 14, pp. 161-166, 2015. ISBN: 978-989-8533-44-9.
[5] M. Keith and M. Schincariol, “Pro JPA 2”. Apress Media LLC, New
York, USA, 2013. ISBN: 978-1-4302-1956-9.
[6] Z. Wadia, H. Saleh, A. L. Christensen, “Pro JSF and HTML5: Building
Rich Internet Components”. Apress Media LLC, New York, USA, 2013.
ISBN: 978-1-4302-5010-4.
[7] PrimeTek Informatics, “PrimeFaces”. 2015 (online). Available:
http://primefaces.org. (30 November 2015).
@article{"International Journal of Information, Control and Computer Sciences:71773", author = "Radek Malinský and Ivan Jelínek", title = "The Visualizer for Real-Time Analysis of Internet Trends", abstract = "The current web has become a modern encyclopedia,
where people share their thoughts and ideas on various topics around
them. This kind of encyclopedia is very useful for other people who
are looking for answers to their questions. However, with the
growing popularity of social networking and blogging and ever
expanding network services, there has also been a growing diversity
of technologies along with a different structure of individual web
sites. It is therefore difficult to directly find a relevant answer for a
common Internet user. This paper presents a web application for the
real-time end-to-end analysis of selected Internet trends where the
trend can be whatever the people post online. The application
integrates fully configurable tools for data collection and analysis
using selected webometric algorithms, and for its chronological
visualization to user. It can be assumed that the application facilitates
the users to evaluate the quality of various products that are
mentioned online.", keywords = "Trend, visualizer, web analysis, web 2.0.", volume = "9", number = "12", pages = "2525-5", }