Mining the Social Web: Analyzing Data from Facebook, by Matthew A. Russell

By Matthew A. Russell

Fb, Twitter, and LinkedIn generate an incredible quantity of beneficial social info, yet how will you discover who is making connections with social media, what they’re speaking approximately, or the place they’re situated? This concise and functional ebook exhibits you the way to respond to those questions and extra. you will tips on how to mix social net info, research suggestions, and visualization that will help you locate what you have been searching for within the social haystack, in addition to worthy details you did not understand existed. every one standalone bankruptcy introduces concepts for mining facts in numerous components of the social net, together with blogs and e mail. All you want to start is a programming history and a willingness to benefit simple Python instruments.

Show description

Read or Download Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites PDF

Similar data mining books

Data Mining in Agriculture (Springer Optimization and Its Applications)

Data Mining in Agriculture represents a entire attempt to supply graduate scholars and researchers with an analytical textual content on facts mining options utilized to agriculture and environmental comparable fields. This ebook provides either theoretical and useful insights with a spotlight on proposing the context of every facts mining method really intuitively with abundant concrete examples represented graphically and with algorithms written in MATLAB®.

Data Mining: Foundations and Practice

This booklet includes useful experiences in information mining from either foundational and useful views. The foundational experiences of information mining may also help to put a fantastic beginning for info mining as a systematic self-discipline, whereas the sensible stories of knowledge mining could lead on to new information mining paradigms and algorithms.

Big Data Analytics and Knowledge Discovery: 17th International Conference, DaWaK 2015, Valencia, Spain, September 1-4, 2015, Proceedings

This booklet constitutes the refereed court cases of the seventeenth foreign convention on facts Warehousing and data Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised complete papers awarded have been rigorously reviewed and chosen from ninety submissions. The papers are prepared in topical sections similarity degree and clustering; information mining; social computing; heterogeneos networks and information; information warehouses; movement processing; purposes of huge info research; and large information.

Understanding Complex Urban Systems: Integrating Multidisciplinary Data in Urban Models

This e-book is dedicated to the modeling and realizing of advanced city structures. This moment quantity of knowing advanced city platforms specializes in the demanding situations of the modeling instruments, relating, e. g. , the standard and volume of knowledge and the choice of a suitable modeling procedure. it truly is intended to help city decision-makers—including municipal politicians, spatial planners, and citizen groups—in identifying a suitable modeling strategy for his or her specific modeling requisites.

Extra info for Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites

Example text

As a final observation, the presence of “rt” is also a very important clue as to the nature of the conversations going on. The token RT is a special symbol that is often prepended to a message to indicate that you are retweeting it on behalf of someone else. Given the high frequency of this token, it’s reasonable to infer that there were a large amount of duplicate or near-duplicate tweets involving the subject matter at hand. In fact, this observation is the basis of our next analysis. The token RT can be prepended to a message to indicate that it is being relayed, or “retweeted” in Twitter parlance.

For rt_source in rt_sources: ... add_edge(rt_source, tweet["from_user"], {"tweet_id" : tweet["id"]}) ... info Figure 1-1. A distribution illustrating the degree of each node in the graph, which reveals insight into the graph’s connectedness The built-in operations that NetworkX provides are a useful starting point to make sense of the data, but it’s important to keep in mind that we’re only looking at a very small slice of the overall conversation happening on Twitter about SNL—500 tweets out of potentially tens of thousands (or more).

Org community had just celebrated its fifth birthday, and Google reported that 94% of the time, microformats are involved in Rich Snippets. If Google has anything to say about it, we’ll see significant growth in microformats; in fact, according to ReadWriteWeb, Google wants to see at least 50% of web pages contain some form of semantic markup and is encouraging “beneficial peer pressure” for companies to support such initiatives. Any way you slice it, you’ll be seeing more of microformats in the future if you’re paying attention to the web space, so let’s get to work.

Download PDF sample

Rated 4.35 of 5 – based on 14 votes