Extract and summarize text from a travel blog and tweet with the identified hashtags
Extract and summarize text from a travel blog and tweet with the identified hashtags to reach target traveler audiences using latent Dirichlet allocation topic modeling
Growing a real following on Twitter takes more than sending out Tweets whenever your company has a product being released or an upcoming event. It’s about engaging with your target audience and interacting with them. Hashtags are important in doing so. This code pattern focuses on extractive summarization of a travel blog, extracting keywords, converting them to relevant hashtags, and tweeting it on Twitter to expand their business through social media marketing.
Successful Twitter marketing is powerful. You can unlock new opportunities to grow your business online. If Twitter is used well, it can drive a lot of traffic to your website. But you must be creative when crafting tweets to promote your blog posts, videos, and other content.
As an example to show how you can market and grow your business, we use a website called hostelgeeks.com, which shares stories of the people who have traveled or visited the places listed in their travel blogs. Sharing experiences with other people does two things. First, any travel blog makes people aware of different locations and can excite people to want to visit that location. Second, reviews and comments about a location from a reliable source provides credibility of that location, which travelers look for before making travel plans. In our example, we ran text summarization on the stories, converted them to meaningful, impactful tweets, and tweeted them using the Twitter API along with relevant hashtags.
- User logs in to Watson Studio and creates an instance that includes IBM Object Storage.
- User uploads the data file to the Object Storage.
- User imports a Jupyter Notebook from the URL.
- User runs the processing techniques and creates a statistical model for the topics in the Notebook.
- User explores the visualization in the Notebook and can export the output to Object Storage.
Find the detailed steps for this pattern in the README file. The steps show you how to:
- Create an account with IBM Cloud.
- Create a new Watson Studio project.
- Create the notebook.
- Add the data.
- Get access tokens and the consumer key to use the Twitter API.