Helps the advertiser’s for pushing the advertisement and series makers for making quick analysis.
Pulling the data helps them in predicting the TRP which in result helps the series makers and advertisers.
As a result of COVID-19 most of the people settled back in their homes lacking entertainment.
All over the world.
Most of the people believe in IMDB rating rather than genre concept.
The dataset is about the web series data where we sampled the tv shows, web series, Netflix series. The information disclosed about the shows watching around the world. Helps the advertiser’s for pushing the advertisement and series makers for making quick analysis.
The events like which show is being watched more an where it is being watched and which kind of people are watching are seen. It helps advertisers in pulling the data helps them in predicting the TRP which in result helps the series makers and advertisers.
The events take place on how people react to the series they tweet. As a result of COVID-19 most of the people settled back in their homes lacking entertainment.
All over the world. As everyone in the world haves an interest on web series and this data is being used everywhere. Thus, we are working on this data taking this into consideration.
Most of the people believe in IMDB rating rather than genre concept. That is the reason behind doing this web series data collection.
(Scientist and AI)
People who watch web series which make them feel comfortable.
Collected the data using python as json file which we visualized by various platform, Finally, hosted in docker.
Data of 2019 in all over the world collected with various hash tags related to web series of Netflix, prime, Hulu.
After getting the data. Later, Visualized the data using spark, solr, hive. Related to PB and BDP.
Helps to understanding the data by visualizing the data stream pulled from twitter.
The set of people who are having free time and interested to watch the series can access the info.
Helps to Visualize the Data or impact of series on the current society based on various features/attributes.
Based on the Data available on the hosted index, user can get the contrast between the OTT platforms and the web series and their pulse among.
Deployed to docker and can host on EC2 instance.
Make’s aware of types of OTT platforms impact on the society.
Users who are mostly spends their time on watching online series. Types of OTT platforms are sampled. No data is sampled.
This data which makes aware of the current situation about the OTT platforms, which mostly doesn’t have social or cultural impacts but only have idea about the OTT platforms. As the data grabbed from the twitter streaming will have security reasons.
If the tweets pulled based on the hashtags which web series related to region, caste, cultural can create positive or negative impact on the social or cultural but mostly it creates the negative impact which may breach the security.
Impact will be on the users who mostly rely on web series. If the Data collected concentrated on the particular set of webseries can cause the evaluative bias.
At current pandemic situation it will be consequential to people who are misled by the various paid platforms which give the review of the series.