By Huan Liu, Shamanth Kumar, Fred Morstatter
This short presents tools for harnessing Twitter facts to find options to advanced inquiries. The short introduces the method of gathering info via Twitter’s APIs and provides ideas for curating huge datasets. The textual content provides examples of Twitter facts with real-world examples, the current demanding situations and complexities of creating visible analytic instruments, and the easiest techniques to handle those concerns. Examples reveal how robust measures might be computed utilizing a variety of Twitter info assets. because of its openness in sharing info, Twitter is a first-rate instance of social media within which researchers can be certain their hypotheses, and practitioners can mine attention-grabbing styles and construct their very own functions. This short is designed to supply researchers, practitioners, venture managers, in addition to graduate scholars with an access aspect to leap commence their Twitter endeavors. It additionally serves as a handy reference for readers professional in Twitter facts research.
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This short presents equipment for harnessing Twitter info to find options to complicated inquiries. The short introduces the method of amassing info via Twitter’s APIs and gives recommendations for curating huge datasets. The textual content supplies examples of Twitter info with real-world examples, the current demanding situations and complexities of creating visible analytic instruments, and the easiest thoughts to handle those concerns.
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Additional resources for Twitter Data Analytics (SpringerBriefs in Computer Science)
GetID())). getWeight() / sum). 2 Sentiment Analysis Often its not important to know what users are saying, but how they are saying it. “Sentiment analysis” seeks to automatically associate a piece of text with a “sentiment score”, a positive or negative emotional score. Aggregating sentiment can give an idea of how people are responding to a company, product, or topic. 1 Sentiment Analysis Overview Sentiment analysis, is done on a per-Tweet basis. The words in each Tweet are compared with those in other Tweets that have been previously labeled as “positive”, 46 4 Analyzing Twitter Data Lexicon Positive p( ) ows max Negative p( ) p( ) Fig.
Create a folder called data next to the mongodb folder. 2 Setting Up MongoDB on a Single Node 25 4. Create a folder called db within the data folder. Your file structure should reflect that shown below. / mongodb ... 2 Running MongoDB on Windows 1. Open the command prompt and move to the directory above the mongodb folder. 2. exe-dbpath data\db 3. If Windows prompts you, make sure to allow MongoDB to communicate on private networks, but not public ones. Without special precautions, MongoDB should not be run in an open environment.
This data explosion calls for a new data storage paradigm. At the forefront of this movement is NoSQL , which promises to store big data in a more accessible way than the traditional, relational model. There are several NoSQL implementations. In this book, we choose MongoDB1 as an example NoSQL implementation. We choose it for its adherence to the following principles: • Document-Oriented Storage. MongoDB stores its data in JSON-style objects. This makes it very easy to store raw documents from Twitter’s APIs.