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

White or Blue, the Whale gets its Vengeance: A Social Media Analysis of the Blue Whale Challenge

The Blue Whale Challenge - a set of tasks that must be completed in a duration of 50 days - is an online social media rage. The tasks of the “game” cause both physical and mental harm to the players; the final task is to take his/her own life. The tasks include waking up at odd hours, listening to psychedelic music, watching scary videos, inflicting cuts and wounds on their bodies and the final task is to commit suicide. The game is supposedly administered by people called “curators” who incite others to take the challenge, brainwash them to cause self harm and ultimately commit suicide. Most conversations between curators and players are suspected to take place via direct message but, in order to find curators, the players need a public platform where they can express their desire to play the game - knowingly or unknowingly. Online social media serves as this platform as people post about not just their desire to be a part of the game but also details and pictures of the various task…

Social Bot Detection on Twitch

Twitch is the leading world live streaming video platform for the Gamer’s community. It is a very famous networking site and has close to 100 million monthly unique users. Bots are very prominent on the network due to various financial favors that the gaming platform provides to a user. The main objective of our Project is Detecting Social Bots on Twitch using various techniques such as Meta-data Analysis, Sentiment analysis from Chats on a Channel, and classification using Machine learning.
We started by collecting usernames of 510 channels for which we compared chatters and viewers on that channels live video. We got 51 channels which had chatters>viewers. On those channels, we did Temporal analysis for over a period of 4 weeks. Alongside, we collected their metadata, such as, Follower, Followings, Status, Partner, and total views. We calculated a Score using these features, from which we could conclude that higher the score, higher the probability of an account being a Bot accoun…

Privacy Concerns on Tinder

Introduction
Mobile dating apps have become a popular means to meet potential partners. Mobile dating application such as Tinder have exploded in popularity in recent years. Most users on Tinder use/have used Facebook as their primary way to sign up. By doing this, Tinder automatically takes user information directly from Facebook, thus saving the need to authenticate the user and user details.  In this project we aim to identify a Tinder profile on Facebook using the information that tinder obtains from Facebook. Below is the information that Tinder takes from a user when they log in for the first time.