Skip to main content

SteemEarn - Get the most out of the content you write online

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).

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

Comments

Popular posts from this blog

Identifying Tinder Profiles on Facebook

Identifying Tinder Profiles on Facebook In the online world, everything that you ever put is linked and connected. You might think that you’ve put some information on one platform and that’s it, you’re good to go. But you, my friend, are sadly mistaken. With this thought in mind and the privacy concerns linked with Online Social Media, we would like to introduce you to our problem statement: Identifying Facebook Profiles from Tinder Profiles. Given a tinder profile, our aim is to identify the corresponding Facebook profile of that person. We are addressing the linkability issue here and trying to highlight how more information than what you’ve mentioned on Tinder can be picked up from your Facebook profile. For those who don’t know, Tinder is a Dating Platform available for a Mobile Application and a Web App. It shows the geographically close profiles around you and you have an option to right swipe(Like) or left swipe(Dislike) them. When two people right swipe each other then it’

iFROOSN: Incentivised Fake Reviews On OSNs with Yelp as the reference

Yelp is an OSN primarily used to popularise the businesses and give reviews about those business. Yelp can be used as an efficient business expander for many upcoming restaurants/spas/saloons who always look for new customers. Problem Statement Our main objective of this course project was to target fake/incentivised reviews on yelp and give a credibility score using which a new user of Yelp can get an overall estimate about the restaurant he/she will visit .We developed an application which required an business ID of yelp as an input and it gave the credibility score as the output along with some inferred results in form of graphs Dataset The primary requirement before starting the project was collecting dataset for Yelp business and corresponding reviews and details about the user which post these reviews .The dataset was obtained through Yelp dataset challenge which was available for academic usage and result collections .The database had predefined schema and

Privacy Control

Online social networks have become an important part of our social lives, and their inherent privacy problems have become a major concern for users. As of March 2016, 142 million Indians maintain a social network profile on Facebook and 30 million on Twitter, which provides them with a convenient way to communicate with family, friends and even total strangers. The Services provided by social media though add convenience to our life to a great extent and have made the world a much closely connected, this boon comes with few hidden problems. Though social media lets users share a part of our life to the world, it also gives birth to the security threats to our personal information.  The users are confronted with a dichotomy between sharing information with their loved ones and friends and sharing information with everyone else on the internet. To help users tackle this dilemma, social networks provide a plethora of privacy settings which allow the user to control his/her pri