Knowledge Retrieval and Semantic Systems

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Suggested Prototype Software to Extract Data from Social Media

Document Type : Research Paper

Authors

1 Assistant Professor, Knowledge and Information Science Department, Shahid Beheshti University, Tehran, Iran

2 International Institute of Earthquake Engineering and Seismology, Tehran, Iran

3 M.A. of Knowledge and Information Science, Shahid Beheshti University, Tehran, Iran

Abstract

In present paper social media archiving software were studied.  In this study, data gathering was done through documentary study and analytical survey.  To evaluate whether or not each software capability was used, the CIR method, the exploratory factor load, and the confirmatory factor load were used; the acceptance of each capability was assessed by a median (mid-range criterion 3). Then, each item was ranked based on the mean of the Friedman test. In the second stage, the CIR of each capability, and in the last stage, the confirmatory factor and the exploratory factor load. Research questions were analyzed using one-sample t-test. Advanced archive search capabilities, "archive categorization (easy browsing)" and "visual reporting" are the most important software requirements for experts. T Advanced archive search, archive categorization (easy browsing), and visual reporting capabilities are the most important software requirements for experts. The ability to "obtain credit certificates from public and private institutions" is of the least importance to experts. Criteria "Automatically delete archives at specified time", "Reset deleted records", "Open archive for public access", "Obtain credentials from public and private entities", "Automatically delete archives at defined time", "Get Version" Complete After Payments "and" Demo Version "can be removed from software capabilities. However, when looking at current data mining software from social networks, some of these capabilities are of great importance. Experts" local storage capability" was added to the final checklist.

Keywords

References
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Knowledge Retrieval and Semantic Systems
Volume 7, Issue 25
January 2021
Pages 1-32
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