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. I. INTRODUCTION N recent years, the Internet has been experiencing a huge boom in social networking, blogging and discussing on online forums, and this is mainly due to the desire of users to share their thoughts and opinions on various topics, products and events around them. This development phase of the web, collectively Web 2.0, has reached to a such stage, where it is quite usual for ordinary users to share their opinions publicly online. Many web services are gradually adapting to this trend, and for instance, online shops allow for consumers to post comments on goods they bought. This facilitates the target customer in making the decision to purchase, the seller gets quick feedback on the goods and the producer determines what to improve on his products. However, it is not easy to analyze such comments when they are on multiple sources. Web services diversity, a variety of technologies along with a different structure of individual web sites, all of these make the analysis of public opinions very difficult. Hence, it is difficult to get accurate feedback on product issues from multiple data sources for an ordinary user, as well as for a commercial company. It is therefore necessary to design a suitable metric for these various data sources that would reflect the semantic content of single pages in the better way and thereby improve a machine understanding of a text. Our research is focused on the development of the web R. Malinský, I. Jelínek are with the Department of Computer Science and Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Karlovo náměstí 13, 121 35 Prague, Czech Republic, (e-mail: malinrad@fel.cvut.cz, jelinek@fel.cvut.cz). application, which brings together metrics for analysis and evaluation of Internet trends. Event, product name, name of the person or any expression, which is mentioned online, all of these can be defined as the Internet trend. Such trend assessment provides a chronological insight into a public opinion on specific search topic; for instance, the opinion on price, quality or other factors of any product, or information about the geographic spread of any article or event. II. RELATED WORK Web search engines are the easiest way to find specific information in such diversified network for ordinary users. However, the search engines just return a list of web sites relevant to the user's search query and they do not provide any direct answer. The user is therefore forced to browse the individual sites and search for answers through consolidation of useful information from them. The user's search queries can serve as a treasure for web data mining because they reflect the ideas of many users. Google started digging into this data source and revealed the service Google Trends. Google Trends reports a chronological summary of trend volume based on queries that people entered into the Google search engine. Numerous studies have been done that used Google Trends as a data source to reveal various types of information like a detection of influenza epidemic [1], prediction of economic indicators [2] or a state politics research [3]. Those studies reflect what people are searching for; however, they do not express what people think about what they are looking. Many complex solutions to resolve public opinion are usually tailored to a specific purpose or data type. There is currently no widely acceptable solution for a trend analysis in such heterogeneous environment the Web 2.0 is. Based on our research, we have revealed a web-based visualizer, which is an extension of the proposed framework [4] and thereby completes the application with end-to-end approach for a real-time analysis and monitoring of selected Internet trends on various data sources. The integrated trend visualizer allows fully configurable possibilities from collection of data from relevant web sources, through its analysis using selected algorithms, to a chronological view of analyzed data to users. Radek Malinský, Ivan Jelínek The Visualizer for Real-Time Analysis of Internet Trends I World Academy of Science, Engineering and Technology International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol:9, No:12, 2015 2481 International Scholarly and Scientific Research & Innovation 9(12) 2015 scholar.waset.org/1999.4/10003285 International Science Index, Computer and Information Engineering Vol:9, No:12, 2015 waset.org/Publication/10003285