Search keyword selection for crawling tweets based on the keyword extraction

dc.contributor.advisorKim, Yanggon
dc.contributor.authorKim, Jeongwoo
dc.contributor.departmentTowson University. Department of Computer and Information Sciencesen_US
dc.date.accessioned2016-03-01T21:58:16Z
dc.date.available2016-03-01T21:58:16Z
dc.date.issued2016-03-01
dc.date.submitted2015-12
dc.description(M.S.) -- Towson University, 2015.
dc.description.abstractAs use of Social Network Services (SNSs) has been increased over and over, demands to derive meaningful information from them are continuing. In order to extract meaningful information from SNSs, to collect data from them should come up on a first step. In the data collection, keyword-based search is widely used to collect data from SNSs using Application Programming Interface (API). However, in this data collection, a lot of extraneous data can be collected according to a selected topic. For example, if using the topic term such as “Coach” (Fashion company) as a search keyword, extraneous data unrelated to the topic are collected as well because term “Coach” is homonym. This problem makes the data analysis more difficult and causes a waste of data storage space. Additionally, it causes a waste of limited resources to collect data such as search queries. For the topics in which the topic term is homonym, more terms for search keywords must be needed in order to collect data more accurately. Also, the terms should be extracted based on the real data. In this thesis, we propose a method to extract search keywords to be effective for collecting data related with a topic using tweets.en_US
dc.description.urihttp://library.towson.edu/cdm/ref/collection/etd/id/46333en_US
dc.formatapplication/pdf
dc.format.extentviii, 45 pagesen_US
dc.genrethesesen_US
dc.identifierdoi:10.13016/M2ZF0T
dc.identifier.otherTF2015Kim
dc.identifier.urihttp://hdl.handle.net/11603/2391
dc.language.isoen_USen_US
dc.titleSearch keyword selection for crawling tweets based on the keyword extractionen_US
dc.typeTexten_US

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