How Long to Read Using Twitter Data and Machine Learning to Identify the Attributes of Social Media Reputation

How Long Does it Take to Read Using Twitter Data and Machine Learning to Identify the Attributes of Social Media Reputation?

It takes the average reader to read Using Twitter Data and Machine Learning to Identify the Attributes of Social Media Reputation by Xiaoqun Zhang

Assuming a reading speed of 250 words per minute. Learn more

Description

This case study explains the research process of how the author furthers media reputation research using Twitter data. 50 of Fortune 500 companies are selected as the company sample, and the tweets about these companies are extracted via Twitter API and Postman platform. A state-of-the-art machine learning approach--Bidirectional Encoder Representations from Transformers (BERT) based model--is used to conduct topic analysis that creates the major attributes of media reputation from the tweets of the sample companies. The readers will learn the techniques to extract data from Twitter using API and Postman, as well as the techniques to apply BERT topic model to conduct aspect analysis. These techniques can not only be used in media reputation research, but also in other corporate communication areas such as brand images, customer reviews, and public relations.

How long is Using Twitter Data and Machine Learning to Identify the Attributes of Social Media Reputation?

Using Twitter Data and Machine Learning to Identify the Attributes of Social Media Reputation by Xiaoqun Zhang is 0 pages long, and a total of 0 words.

This makes it 0% the length of the average book. It also has 0% more words than the average book.

How Long Does it Take to Read Using Twitter Data and Machine Learning to Identify the Attributes of Social Media Reputation Aloud?

The average oral reading speed is 183 words per minute. This means it takes to read Using Twitter Data and Machine Learning to Identify the Attributes of Social Media Reputation aloud.

What Reading Level is Using Twitter Data and Machine Learning to Identify the Attributes of Social Media Reputation?

Using Twitter Data and Machine Learning to Identify the Attributes of Social Media Reputation is suitable for students ages 2 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

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