[Notice] Check out the new TEXTOM Analysis Report on 'Naver Premium Content'!

-

Check out the new TEXTOM Analysis Report on 'Naver Premium Content'!👋




📌What is Naver Premium Content?👀


"Naver Premium Content" is a new paid content service on the Naver platform that allows users to subscribe to a variety of content provided by experts, influencers, or creators with specialized knowledge. Content includes Writing, images, videos, and more, often delivering in-depth information and premium resources in specific fields. This service enables users to receive customized content on topics of interest, with continuous updates that keep them informed and engaged.


📌Approval for Naver Premium Content Homepage Launch🎉

Going forward, you'll be able to explore a variety of analysis reports on Naver Premium Content using Textom. These reports will be available in two formats: the Textom Global Report and the Textom Marketing Brief.
Our first post on Naver Premium Content covers the 2024 U.S. presidential election. Using Textom's Text data analysis, we've crafted a report predicting who the potential winner of the 2024 election might be. This analysis examines the ETI trends of Trump and Harris to forecast the election outcome. If you're curious about who big data points to as the likely winner in the 2024 U.S. presidential election, check out the Global Report now!

From November, we will publish a marketing brief using Textom's English data. Please continue to pay attention to Textom's content in Naver Premium Content.







Comments

Post a Comment

Popular posts from this blog

[TEXTOM Manual] TF-IDF value calculation formula

-
Image
The TF-IDF calculation formula provided by TEXTOM is as follows: TF : Term Frequency - the frequency of the word ln : Natural logarithm D : Total number of documents DF : Number of documents containing the word TF-IDF (Term Frequency – Inverse Document Frequency) is a statistical measure indicating how important a word is in a specific document among a set of documents. It is often used in conjunction with morphological analysis. It is an algorithm that assigns scores to all words used in a sentence. The higher the word frequency in a specific document and the lower the number of documents containing the word in the entire set of documents, the higher the TF-IDF value. Therefore, using this value, common words that appear in all documents can be filtered out, and the key terms of the document can be extracted. - TF (Term Frequency): Represents how often the word appears in the entire document. - IDF (Inverse Document Frequency): Represents the reciprocal of DF, i.e., the total numb
Read more

[Notice] TEXTOM Global Launch Time Announcement

-
Image
🎉TEXTOM Global Grand Open🎉 Hello! We are excited to announce the launch of "TEXTOM Global" on February 1st, 2024. We sincerely appreciate the support of our members. The global version caters to all English-speaking countries, For those who have struggled with writing English papers utilizing Big Data! For those who want to analyze Big Data with English datasets! Everyone can easily perform Big Data analysis. Following the Korean and Chinese versions, we kindly ask for your interest and support in the global version. ▼ Start using TEXTOM now ▼ https://textom.global/ TEXTOM is committed to providing the best service at all times. Thank you.
Read more