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Solomon Messing

I direct the Pew Research Center's Data Labs. My research interests include elite communication and politics, constituent communication, social media, political advertising and campaigns, race, machine learning, experiments, networks, text as data, etc. My work has appeared in Science, the Princeton University Press, the American Political Science Review, Public Opinion Quarterly, Scandinavian Political Studies, Radiology, Pediatric Radiology, and has been covered in the New York Times, the Washington&h

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I direct the Pew Research Center's Data Labs. My research interests include elite communication and politics, constituent communication, social media, political advertising and campaigns, race, machine learning, experiments, networks, text as data, etc. My work has appeared in Science, the Princeton University Press, the American Political Science Review, Public Opinion Quarterly, Scandinavian Political Studies, Radiology, Pediatric Radiology, and has been covered in the New York Times, the Washington&h
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Solomon Messing | solomonmessing.wordpress.com Reviews

https://solomonmessing.wordpress.com

I direct the Pew Research Center's Data Labs. My research interests include elite communication and politics, constituent communication, social media, political advertising and campaigns, race, machine learning, experiments, networks, text as data, etc. My work has appeared in Science, the Princeton University Press, the American Political Science Review, Public Opinion Quarterly, Scandinavian Political Studies, Radiology, Pediatric Radiology, and has been covered in the New York Times, the Washington&h

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January | 2014 | Solomon Messing

https://solomonmessing.wordpress.com/2014/01

Monthly Archives: January 2014. Visualization Series: Using Scatterplots and Models to Understand the Diamond Market. January 19, 2014. My last post railed against the bad visualizations that people often use to plot quantitive data by groups, and pitted pie charts, bar charts and dot plots against each other for two visualization tasks. Dot plots came out on top. … Continue reading →. Exposure to Ideologically Diverse News and Opinion, Future Research. When to Use Stacked Barcharts?

2

May | 2015 | Solomon Messing

https://solomonmessing.wordpress.com/2015/05

Monthly Archives: May 2015. Exposure to Ideologically Diverse News and Opinion, Future Research. May 24, 2015. Eytan Bakshy and Solomon Messing Earlier this month, we published an early access version of our paper in ScienceExpress (Bakshy et al. 2015), Exposure to ideologically diverse news and opinion on Facebook. The paper constitutes the first attempt to quantify … Continue reading →. Exposure to Ideologically Diverse News and Opinion, Future Research. When to Use Stacked Barcharts?

3

Teaching | Solomon Messing

https://solomonmessing.wordpress.com/teaching

Political Communication and Social Media. Communication 102S), Summer 2013. Political Science 452 CA for Justin Grimmer. Campaigns, Voting, Media and Elections. Political Science 120B/Communication 162/262, TA for Shanto Iyengar. Computers and Interfaces (Communication 169/269/Symbolic Systems 169/269/Sociology 133/233/STS 162/262, TA for Cliff Nass. Media Processes and Effects (Communication 108/208, TA for Jeremy Bailenson. Stanford Computational Social Science Workshop:. Scraping Web Data and Text.

4

June | 2013 | Solomon Messing

https://solomonmessing.wordpress.com/2013/06

Monthly Archives: June 2013. Streamline Your Mechanical Turk Workflow with MTurkR. June 24, 2013. I’ve been using Thomas Leeper‘s MTurkR package to administer my most recent Mechanical Turk study—an extension of work on representative-constituent communication claiming credit for pork benefits, with Justin Grimmer and Sean Westwood. MTurkR is excellent, making it quick and easy to: test … Continue reading →. Exposure to Ideologically Diverse News and Opinion, Future Research. Blog at WordPress.com.

5

Software/Code | Solomon Messing

https://solomonmessing.wordpress.com/softwarecode

Labs for Social Network Analysis using R (with Dan McFarland, Mike Nowak, and Sean Westwood). 8211; Adaptation of Dan McFarland’s labs for Social Network Analysis to R (most labs previously relied on UCINet). R package to analyze image data, designed to facilitate analysis described in “Bias in the flesh.” Package. An R package to produce violin plots with weighted data, which. Allows the visualization of the distribution of a quantitative variable. Plot is a combination box plot and kernel density plot.

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GivenTheData: September 2012

http://giventhedata.blogspot.com/2012_09_01_archive.html

Thursday, September 13, 2012. Estimating Pi with R via MCS-Dart: A very simple example of numerical integration, illustrated and computed in R. Have you ever played Monte Carlo Dart? If not, read this post and learn how to do it with R and what it can be used for. In fact it is a very easy and prevalent example (which I have come across in a computational economics course. To draw the circle. Emptyplot(c(0, 0),frame.plot=r). Plotcircle(r=r, mid=c(0,0), lwd=1,lcol="blue"). Lines(x=c(-1,1),y=c(0,0), lty=2).

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GivenTheData: My R-Package Development Cheat Sheet

http://giventhedata.blogspot.com/2013/02/my-r-package-development-cheat-sheet.html

Thursday, February 7, 2013. My R-Package Development Cheat Sheet. In case you have no experience in writing an R-package yourself but would like to start developing one right away, this post might be helpful. From my github repo):. This was contributed by giventhedata.blogspot.com #. I Very useful tools when writing a R-package:. Assuming your package is to be called 'MyRpackage' and. All the scripts that contain functions that should be part. Of your package are in your current working directory and.

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GivenTheData: R and the web (for beginners), Part I: How is the local nuclear plant doing?

http://giventhedata.blogspot.com/2012/06/r-and-web-for-beginners-part-i-how-is.html

Thursday, June 21, 2012. R and the web (for beginners), Part I: How is the local nuclear plant doing? One of the things I especially like about R is its ability to easily access and process data from the web. If you are new to R, or never have used it to access data from the Internet, here is the first part of a little series of posts with examples to get you started. This first post gives a very simple example of. How to access a data set that is saved online. How to access that data directly through R?

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The Silent Observer: June 2015

http://theunsweptcorner.blogspot.com/2015_06_01_archive.html

A blog about anything. Monday, June 22, 2015. I wish I knew how to change the thumbnail image on youtube. Anyway, can only do so much ass-saving with a face like mine. Subscribe to: Posts (Atom). Macro and Quant Finance. Laeeth Isharc - Quora Answers. Ruchir Sharma - Foreign Affairs. John Cochrane - The Grumpy Economist. Clifford Asness - Cliff's Perspective. James Picerno - Capital Spectator. Rob Carver - Investment Idiocy. Data Science and R. Awesome Inc. template. Powered by Blogger.

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GivenTheData: R and the web (for beginners), Part II: XML in R

http://giventhedata.blogspot.com/2012/06/r-and-web-for-beginners-part-ii-xml-in.html

Friday, June 22, 2012. R and the web (for beginners), Part II: XML in R. This second post of my little series on R and the web deals with how to access and process XML-data with R. XML. Is a markup language that is commonly used to interchange data over the Internet. If you want to access some online data over a webpage's API. You are likely to get it in XML format. So here is a very simple example of how to deal with XML in R. Wrote a very helpful R-package. Taken from w3schools.com. PLANT PLANT COMMON ...

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GivenTheData: R and the web (for beginners), Part III: Scraping MPs' expenses in detail from the web

http://giventhedata.blogspot.com/2012/08/r-and-web-for-beginners-part-iii.html

Thursday, August 23, 2012. R and the web (for beginners), Part III: Scraping MPs' expenses in detail from the web. In this last post of my little series (see my latest post. On R and the web I explain how to extract data of a website ( web scraping. Screen scraping) with R. If the data you want to analyze are a part of a web page, for example a HTML-table (or hundreds of them) it might be very time-consuming (and boring! Web scraping with R. Parse the document for R representation:. As data.frame&#46...

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GivenTheData: March 2013

http://giventhedata.blogspot.com/2013_03_01_archive.html

Thursday, March 14, 2013. Data Science in Business/Computational Social Science in Academia? Lately, the terms "data science" and "data scientist" turn up at an increasing pace in the R-blog-sphere. Since its first occurrence (to my knowledge, "data scientist" has been coined by DJ Patil and Jeff Hammerbacher. As well as some controversial discussions. Empirical Computational Social Science. Published Lazer et al.'s maniphesto. And drafted another Venn-diagram to illustrate how data-driven computational ...

theunsweptcorner.blogspot.com theunsweptcorner.blogspot.com

The Silent Observer: July 2015

http://theunsweptcorner.blogspot.com/2015_07_01_archive.html

A blog about anything. Saturday, July 18, 2015. This is the 18th of July 2015. Nothing happened to me today. Saturday, July 4, 2015. Subscribe to: Posts (Atom). Macro and Quant Finance. Laeeth Isharc - Quora Answers. Ruchir Sharma - Foreign Affairs. John Cochrane - The Grumpy Economist. Clifford Asness - Cliff's Perspective. James Picerno - Capital Spectator. Rob Carver - Investment Idiocy. Data Science and R. Awesome Inc. template. Powered by Blogger.

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The Silent Observer: R for Basic Statistics - 1

http://theunsweptcorner.blogspot.com/2015/02/r-for-basic-statistics-1.html

A blog about anything. Sunday, February 1, 2015. R for Basic Statistics - 1. R for Simulation, Sampling and Inference. Outcomes = c("heads", "tails"). Sim fair coin = sample(outcomes, prob=c(0.4,0.6) , size=100, replace=TRUE). Another use of sample() is to sample n elements randomly from a vector v. To create a vector of size 15 all of whose value are identical:. Vector2=rep(NA, 15). NA is often used as placeholder for missing data in R. For loop in R. For (i in 1:50) {}. Compare to Python (later). Pleas...

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The Silent Observer: Inflection

http://theunsweptcorner.blogspot.com/2015/07/inflection.html

A blog about anything. Saturday, July 18, 2015. This is the 18th of July 2015. Nothing happened to me today. Subscribe to: Post Comments (Atom). Macro and Quant Finance. Laeeth Isharc - Quora Answers. Ruchir Sharma - Foreign Affairs. John Cochrane - The Grumpy Economist. Clifford Asness - Cliff's Perspective. James Picerno - Capital Spectator. Rob Carver - Investment Idiocy. Data Science and R. Awesome Inc. template. Powered by Blogger.

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Solomon Media Productions: Home

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Dr. Solomon Menahem - Nephrologist - Renal Physician - General Medicine

Consultant Physician in Renal and General Medicine. MB BS (Hons.) FRACP PhD. Dr Solomon Menahem is a Nephrologist with over 15 years experience in all areas of renal disease. He works as a Renal Physician in both the public and private sectors. He currently works at the Alfred Hospital in the Renal Unit with access to Caulfield and Sandringham Dialysis units for patients with end stage renal failure. Dr Menahem is also a Senior Lecturer with Monash University with a PhD in IgA Nephropathy.

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Solomon Messing

I direct the Pew Research Center’s Data Labs. My research interests include elite communication and politics, constituent communication, social media, political advertising and campaigns, race, machine learning, experiments, networks, text as data, etc. My work has appeared in. The Princeton University Press. The American Political Science Review. And has been covered in the. Here’s my info: Google Scholar. Email: [firstname.lastname] AT gmail DOT com. Leave a Reply Cancel reply. Enter your comment here.

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