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Twitter, with its short texts and large number of users, zero cost of entry, and open API, has become a social media phenomenon providing an inexpensive way to connect with customers, increase brand awareness, improve product development, and gather competitive intelligence. The key, to take advantage of this information, is to understand the Twitter conversation: who are the influencers; what are they saying when they talk about a person; who should one follow based on what they talk about. This paper discusses the use of text mining, visualization, and the HTTP Procedure to provide a complete understanding of the Twitter conversation.
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