ThinkToStart

[...] two parts: One we need to train the SVM model and one to actually test if it works. The caret package provides a handy function for this task. http://www.inside-r.org/packages/cran/caret/docs/ [...]

[...] You can use this tutorial in the ThinkToStartR package with: token <-ThinkToStart(“Foursquare_auth”,app_name=”R_Test& [...]

[...] You can use this tutorial in the ThinkToStartR package with: ThinkToStart(“SentimentCloud”,”KEYWORD”,# of tweets,” [...]

***ALPHA*** I just started to work on my new package for this blog. This R package will include the code of all my tutorials and will make it accessi [...]

[...] .io/FB_page_analyzer/ Authentication: Like every time we need to go through the authentication process. You can find the steps to do so in the first part of this tutorial: http:// [...]

[...] This tutorial will show you how you create an Instagram app, create an authentication process with R and get data via the Instagram API. There is no R package for this yet so we have [...]

[...] /view/ Like always when we want to work with Twitter we have to go through the authentication process like I described here. And then we need some packages for this tutorial but they [...]

[...] will disappear as soon as you close the R instance. Get all the Data! Ok after the authentication process the fun part can start. First we need to get the data and split the returned JSON [...]

[...] Wordcloud entstand auf Grundlage von 1000 Tweets und einer Sentiment Analyse mit der Datumbox API. Auch wenn nicht jeder Tweet korrekt bewertet sein sollte, gibt es doch ein gutes Gesamtbild [...]

[...] with: ThinkToStart(“SentimentCloud”,”KEYWORD”,# of tweets,”DATUMBOX API KEY”) Hey everybody, some days ago I created a wordcloud filled with tweets of a recent [...]

[...] ask or follow me on Twitter to get the newest updates about analytics with R and analytics of Social Data.                           & [...]

[...] Hello everybody! This post will be about two new things: Using Python for getting Social Data and working with the LinkedIn API and is based on Matthew A. Russell´s book “Mining [...]

[...] or to identify networks of customers and influencers. So Big Data will help to make more use of social data by combining internal and external, structured and unstructured data sources to improve [...]

[...] by the ratio of their followers and how many people they follow. Setup Before we can get the Twitter data we have to authorize like I described here. But before we go one we make sure that we have [...]

[...] you can find here: and load it with: Then we just have to set this list as the names of our dataset data frame with: In the next step we transform the y column, which is numeric at the moment, to [...]