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extension
  • NetMiner Extension is small program to extend the functionality of NetMiner. In other words, it enables you to customize NetMiner according to your needs. By adding ‘NetMiner Extension’, you can expand your research.

[Brochure] NetMiner Extension

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Extensions

SNS Data Collector

  • NetMiner SNS Data Collector collects data from Facebook, YouTube, Twitter or Instagram which have large number of SNS users worldwide. You can see public opinion on specific issues or organizations. Also it can identify opinion leaders.
  • Collect Social Media Data
  • It collects data from Facebook, Twitter, YouTube and Instagram. It allows you to identify public opinion on specific issues and analyze the message of a brands. Also you can figure out what people are saying about a particular area or attractions in Instagram. Within a few clicks, you can collect social media data whenever you need.
  • Text Mining for Social Media
  • It can extract words from the text(e.g. tweets, titles of videos, posts, comments) and get a word network and visualize it. Also, TF-IDF and Frequency can be used for filtering data and ‘Word Cloud(Tag Cloud). In addition, you can identify topics using ‘Topic modeling’.
  • Extract Various Networks from Social Media
  • Social media contains various network can be visualized and analyzed. For instance, it creates user-to-user retweet network if a user retweet another user’s tweet. Besides, it provides various networks such as user-to-post network, user-to-word network.

    Biblio Data Collector

    • NetMiner Biblio Data Collector can collect bibliographic information directly from online or import the paper bibliographic information files that have been already collected and saved from other sites such as Web of Science, SCOPUS.
  • Collect Bibliographic Data from Online
  • With search keywords, you can collect bibliographic information directly from online(2019.02. Springer, KCI are supported). Or it can import the bibliographic information files(*.ris) that have been saved from several bibliographic database.
  • Offer Preprocessing Options for Author and Text
  • In research trend analysis, the preprocessing is complicated and time consuming jobs. It can extract keyword from text(title, abstract)(More >>) and reduce the extra process. For example, author keywords can be registered as proper noun. And it helps distinguish authors with same name based on the related bibliographic information.
  • Extract Various Networks from Bibliographic information
  • It can easily extract a variety of network(e.g. co-word network, co-authorship network between authors, affiliations and keyword co-occurrence network) from bibliographic data.