A machine learning platform that has video content analysis capability can harness intelligence from video and audio data. This lets you get even deeper YouTube insights by analyzing not only comments and hashtags but the videos themselves. These could be multiple videos or any particular one. There are six stages in which YouTube video analysis happens.

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2. Table of Contents
● From Which Sources Does A YouTube Video Analytics Tool
Gather Data?
● How Does YouTube Channel Analytics Work Within Your
Profile?
● How Do We Get YouTube Insights From Comments &
Hashtag Analysis?
● How We Do YouTube Video Analysis?

3. From Which Sources Does A
YouTube Video Analysis Tool
Gather Data?

4. A TikTok analytics tool allows you to gain customer insights that go
beyond profile analytics of likes and shares and it does so by data
mining comments and videos. These insights from TikTok for social
listening show you how your customers truly feel about your brand
and products and what their opinions are. Based on this you can
implement the necessary strategies to improve your products or
customer experience and give your customers what they want and
expect. This reflects on a better sales conversion ratio and helps you
generate more profit.

5. 1. Dashboard Analytics - The YouTube dashboard analytics gives you metrics on
key performance indicators like the total number of comments, shares, likes,
dislikes, etc.
2. Comments and Hashtags - This is the source of all the text data comprising
comments as well as hashtags related to your video or videos.
3. Videos - This data source consists of the YouTube video itself. YouTube insights
from this source come from either one video, or all the videos in a particular
channel, or those related to a hashtag or keyword.

6. How Does YouTube Channel
Analytics Work Within Your
Profile?

7. The YouTube Analytics API allows you to create your own custom dashboard from the key performance
indicator data you want from your YouTube channel. These are -
1. Likes count - Number of times your video was liked
2. Dislikes count - Total number of times the dislike button was hit
3. Shares count - How often your video was shared
4. Views count - How many times your YouTube video was watched
5. Comments count - The number of comments your video has gained under it. This includes reply threads
6. View duration - The number of seconds or minutes your video was watched
7. Subscriber count - The total number of subscribers your channel has
8. New subscriber count - How many new subscribers you have gained

8. How Do We Get YouTube Insights
From Comments & Hashtag
Analysis?

9. Insights from YouTube comments and hashtags-related data are a very crucial source of
business intelligence for branding and marketing efforts. Here are the three steps in which
YouTube insights from comments and hashtags is gathered.
Step 1: Data Preparation (comments & hashtags)
First, you need to pre-process the data by cleaning it. You do so by removing all redundant
words, hyperlinks, and non-text data. You can either use the YouTube API to get this data or
a comments scraper - yt-comment-scraper - npm. All this data must be in a .csv file so the
YouTube insights platform can ingest it for processing.

10. Step 2: Processing the data for sentiment
In this step of YouTube video analysis for comments, all the cleaned and prepped data runs through a
sentiment analysis API. It is processed for sentiment after natural language processing tasks have extracted
relevant information about key aspects, themes, and features occurring in the data. Named entity recognition
(NER) ensures that any important named data like a place, brand, important person, currency, etc. is
extracted for sentiment analysis as well.
Step 3: YouTube Insights Visualization
The tool showcases all the insights it has gained after processing the data, in the form of charts, graphs,
color codes, and other visualizations through our sentiment analysis dashboard. You can see how positive,
negative, or neutral the feelings are towards your video, and by extent, your brand. You can also see
sentiment for aspects and features that the tool extracted from your video. For example, color, room, fit,
price, convenience, and such, are aspects.

11. How We Do YouTube Video
Analysis?
A machine learning platform that has video content analysis capability can
harness intelligence from video and audio data. This lets you get even deeper
YouTube insights by analyzing not only comments and hashtags but the videos
themselves. These could be multiple videos or any particular one. There are six
stages in which YouTube video analysis happens.

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