Nowadays, content writing and blogging is a very common activity and many people like journalists and food bloggers make a living out of it. Online blogging websites gives us a very good platform to help us share content easily and effortlessly. We have chosen two content writing networks for our project, Medium and SteemIT.
Medium is the largest content sharing platform in the world with over 480 million views per month where users can share their views in terms of content. In exchange of writing content user just gets popularity and recommendations on Medium. On the other hand, we have chosen SteemIT, which is the largest of its kind platform where you get paid in terms of Steem Currency for writing whenever someone upvotes your post or insert a comment on your post.
So if a writer is good in writing content in several categories, he/she is often confused about which category he should write or start with. Our platform solves this problem by suggesting them the category on which they should write to get maximum return. On Medium, return is in terms of Claps and Recommendations and on SteemIT, it is in terms of Steem Cryptocurrency (In simple language, it is a currency like bitcoin on blockchain network for this purpose only).
We collected data from SteemIT using API provided by SteemIT itself, stored it in our database, analysed it, and displayed the results on our site. If a user have some topics in his mind, our site will help him to decide on which topic he should write so as to get maximum profit. Statistics and historical data for the same will be displayed in form of graphs for which we used google charts api.
Medium is a similar blogging platform and is very famous and has a lot bigger user base than SteemIT. We collected data from medium using scrapping because the api is not provided. We stored the data in our database. We used that information from Medium to compare it to a much smaller platform like SteemIT and displayed the results on our site.
For Security we collected all the links that are in the blogs, stored them and make api calls to check if there is any malicious link in them and displayed the results on our site. We used Google Safe Browsing API for detecting the malicious links.
How we analysed the data – In SteemIT, we collected the data and ranked the topics by their number of upvotes and comments. In medium we have no of claps and recommendation along with comments to help us compare different categories. To show the results we designed a website. We implemented user authentication on our website along with facebook login. We have a search bar to search for topics that the user is interested in and display the graphical representation of the results, giving the recent fluctuations in the popularity of the topic by the help of data collected over the period of time. The user can also add his favorite topics on which he get a live feed on the dashboard.
The results are very helpful in making a difficult choice easier for content writer and bloggers. You can earn smartly by using our app if you are a good content writer.
Medium is the largest content sharing platform in the world with over 480 million views per month where users can share their views in terms of content. In exchange of writing content user just gets popularity and recommendations on Medium. On the other hand, we have chosen SteemIT, which is the largest of its kind platform where you get paid in terms of Steem Currency for writing whenever someone upvotes your post or insert a comment on your post.
So if a writer is good in writing content in several categories, he/she is often confused about which category he should write or start with. Our platform solves this problem by suggesting them the category on which they should write to get maximum return. On Medium, return is in terms of Claps and Recommendations and on SteemIT, it is in terms of Steem Cryptocurrency (In simple language, it is a currency like bitcoin on blockchain network for this purpose only).
Suggestion for Medium from the list of selected categories with SteemEarn Score |
Suggestion for SteemIT from the list of selected categories with SteemEarn Score |
We collected data from SteemIT using API provided by SteemIT itself, stored it in our database, analysed it, and displayed the results on our site. If a user have some topics in his mind, our site will help him to decide on which topic he should write so as to get maximum profit. Statistics and historical data for the same will be displayed in form of graphs for which we used google charts api.
Performance of life category on Medium Platform |
Medium is a similar blogging platform and is very famous and has a lot bigger user base than SteemIT. We collected data from medium using scrapping because the api is not provided. We stored the data in our database. We used that information from Medium to compare it to a much smaller platform like SteemIT and displayed the results on our site.
Performance of life category on SteemIT Platform |
For Security we collected all the links that are in the blogs, stored them and make api calls to check if there is any malicious link in them and displayed the results on our site. We used Google Safe Browsing API for detecting the malicious links.
How we analysed the data – In SteemIT, we collected the data and ranked the topics by their number of upvotes and comments. In medium we have no of claps and recommendation along with comments to help us compare different categories. To show the results we designed a website. We implemented user authentication on our website along with facebook login. We have a search bar to search for topics that the user is interested in and display the graphical representation of the results, giving the recent fluctuations in the popularity of the topic by the help of data collected over the period of time. The user can also add his favorite topics on which he get a live feed on the dashboard.
The results are very helpful in making a difficult choice easier for content writer and bloggers. You can earn smartly by using our app if you are a good content writer.
Technical Stack
- Node JS
- MongoDB
- BootStrap, Google Web Starter Kit, Google Charts
- Hosted on Google Cloud
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