2016•Unpublished venueRequires access

Research of focused crawler for financial social network

Xiaotian Diao

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Abstract

With the rapid rise in social network users during recent years, social network is changing business models in the China's Internet industry. Social network produces large amounts of data that reflect the real world, so we can make conclusions about financial incidents by monitoring people's interests in social network and analyzing investors' feelings based on the data. To obtain the data from financial social networks, crawling the web entirely is expensive and unrealistic because of limited resources. A focused crawler that targets a particular topic is more suitable. This paper implements a focused crawler for collecting pages on the financial social network.

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What this paper is about

With the rapid rise in social network users during recent years, social network is changing business models in the China's Internet industry. Social network produces large amounts of data that reflect the real world, so we can make conclusions about financial incidents by monitoring people's interests in social network and analyzing investors' feelings based on the data. To obtain the data from financial social networks, crawling the web entirely is expensive and unrealistic because of limited resources. A focused crawler that targets a particular topic is more suitable. This paper implements a focused crawler for collecting pages on the financial social network.

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Available abstract

With the rapid rise in social network users during recent years, social network is changing business models in the China's Internet industry. Social network produces large amounts of data that reflect the real world, so we can make conclusions about financial incidents by monitoring people's interests in social network and analyzing investors' feelings based on the data. To obtain the data from financial social networks, crawling the web entirely is expensive and unrealistic because of limited resources. A focused crawler that targets a particular topic is more suitable. This paper implements a focused crawler for collecting pages on the financial social network.

Key concepts: Web crawler, Crawling, Social network (sociolinguistics), Focused crawler, Computer science, World Wide Web, The Internet, Data science

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