Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

October 4, 2019

rtweet (Collecting Twitter Data)

Filed under: R,Twitter — Patrick Durusau @ 2:18 pm

rtweet

A boat load of features and one of the easiest on-ramps to Twitter I have seen:

All you need is a Twitter account (user name and password) and you can be up in running in minutes!

Simply send a request to Twitter’s API (with a function like search_tweets(), get_timeline(), get_followers(), get_favorites(), etc.) during an interactive session of R, authorize the embedded rstats2twitter app (approve the browser popup), and your token will be created and saved/stored (for future sessions) for you.

Add to that high quality documentation and examples, what more would you ask for?

Not that I think Twitter data is representative for sentiment measures, etc., but that’s not something you need to share with clients who think otherwise. If they are footing the bill, collect and analyze the data that interests them.

September 25, 2019

Banned By Twitter

Filed under: Censorship,Free Speech,Twitter — Patrick Durusau @ 7:28 pm

Twitter is vigilant about protecting the feelings of people who deny vaccines for children and even let them die in their custody. I’m speaking of CBP/ICE agents and the following notice I received from Twitter:

Twitter Suspension

Isn’t that amazing? No doubt had Twitter been around when the Brown Shirts and SS were popular, it would be protecting their feelings as well.

Apologies for the long silence! I hope to resume at least daily postings starting with this one.

October 31, 2018

ICC Metadata – Vulnerability Pattern?

Filed under: Steganography,Tweets,Twitter — Patrick Durusau @ 2:07 pm

This Tiny Picture on Twitter Contains the Complete Works of Shakespeare by Joseph Cox.

From the post:


The trick works by leveraging how Twitter handles metadata. Buchanan explained that Twitter strips most metadata from images, but the service leaves a particular type called ICC untouched. This is where Buchanan stored his data of choice, including ZIP and RAR archives.

“So basically, I wrote a script which parses a JPG file and inserts a big blob of ICC metadata,” he said. “The metadata is carefully crafted so that all the required ZIP headers are in the right place.” This process was quite fiddly, he added, saying it took a few hours to complete, although he wrote the script itself over a span of a couple of months.

“I was just testing to see how much raw data I could cram into a tweet and then a while later I had the idea to embed a ZIP file,” Buchanan added.

The ICC link points to PhotoMe:

PhotoME is a powerful tool to show and edit the meta data of image files. Thanks to the well organised layout and intuitive handling, it’s possible to analyse and modify Exif and IPTC-NAA data as well as analyse ICC profiles – and it’s completely FREE!

Useful link/software but it doesn’t define ICC metadata.

I’m curious because the handling of ICC metadata may be a vulnerability pattern found in other software.

ICC metadata is a color profile defined by the International Color Consortium. The ICC specifications page has links to the widely implemented version 4, Specification ICC.1:2010-12 (Profile version 4.3.0.0); its successor, now in development, Specification ICC.2:2018 (iccMAX); and, the previous ICC Profile, Specification ICC.1:2001-04.

The member list of ICC alone testifies to the reach of any vulnerability enabled by ICC metadata. Add to that implementers of ICC metadata and images with it.

How does your image processing software manage ICC metadata?

October 8, 2018

Hurricane Florence Twitter Dataset – Better Twitter Interface?

Filed under: Data,Tweets,Twitter — Patrick Durusau @ 3:56 pm

Hurricane Florence Twitter Dataset by Mark Edward Phillips.

From the webpage:

This dataset contains Twitter JSON data for Tweets related to Hurricane Florence and the subsequent flooding along the Carolina coastal region. This dataset was created using the twarc (https://github.com/edsu/twarc) package that makes use of Twitter’s search API. A total of 4,971,575 Tweets and 347,205 media files make up the combined dataset.

No hyperlink in the post but see: twarc.

Have you considered using twarc to create a custom Twitter interface for yourself? At present just a thought but once you have the JSON, your ability to manipulate your Twitter feed is limited only by your imagination.

Once a base archive is constructed, create a cron job that updates base. Not “real time” like Twitter but then who makes decisions of any consequence in “real time?” You can but its not a good idea.

While you are learning twarc, consider what other datasets you could create.

October 2, 2018

More Free Speech Lost at Twitter

Filed under: Censorship,Free Speech,Hacking,Twitter — Patrick Durusau @ 7:19 pm

Twitter bans distribution of hacked materials ahead of US midterm elections by Catalin Cimpanu.

From the post:


Twitter already had rules in place that prohibited the distribution of hacked materials that contain private information or trade secrets, but after Monday’s update, the platform’s review teams will also ban accounts that claim responsibility for a hack, make hacking threats, or issue incentives to hack specific people and accounts.

Nevertheless, the social network hasn’t been that successful, barely putting a dent in spam-related reports, with the number of complaints going down from 17,000 in May to only 16,000 in September. More work needs to be done, and Twitter just gave its staff sharper teeth to go about their job.

See Cimpanu’s post for the full scope of the damage being done to free speech at Twitter.

Any Twitter investor’s with insight into how much Twitter wastes on its censorship operations every year?

As an investor, I would want to see some ROI from censorship. You?

September 25, 2018

Twitter’s Quest to Police Public Conversation [Note on feminist power analysis]

Filed under: Censorship,Free Speech,Twitter — Patrick Durusau @ 10:05 am

Not satisfied with suppressing the free speech of millions, Twitter is expanding the power of its faceless censors to seek out and silence dehumanizing language.

From their post:


For the last three months, we have been developing a new policy to address dehumanizing language on Twitter. Language that makes someone less than human can have repercussions off the service, including normalizing serious violence. Some of this content falls within our hateful conduct policy (which prohibits the promotion of violence against or direct attacks or threats against other people on the basis of race, ethnicity, national origin, sexual orientation, gender, gender identity, religious affiliation, age, disability, or serious disease), but there are still Tweets many people consider to be abusive, even when they do not break our rules. Better addressing this gap is part of our work to serve a healthy public conversation.

With this change, we want to expand our hateful conduct policy to include content that dehumanizes others based on their membership in an identifiable group, even when the material does not include a direct target. Many scholars have examined the relationship between dehumanization and violence. For example, Susan Benesch has described dehumanizing language as a hallmark of dangerous speech, because it can make violence seem acceptable, and Herbert Kelman has posited that dehumanization can reduce the strength of restraining forces against violence.

Let’s be clear: I don’t tweet, re-tweet or otherwise amplify any of the conduct that is now or would be in the future, forbidden as “dehumanizing language.”

At the same time, it is every user’s right to determine for themselves what content, harmful and/or dehumanizing, they wish to say or view.

Trivially easy for Twitter to implement filters that users could “follow” in order to avoid either harmful or dehumanizing speech, tuned to their specific choices. The same is true for followable block list of users known to spew such nonsense.

For reasons unknown to me, Twitter and its fellow travelers want to police the “public conversation.” So that its nameless and faceless censors can shape the public conversation.

Twitter censorship favors the same values I do, but even so, I find it objectionable in all respects.

If you know anyone working at Twitter, challenge them to empower users with followable content filters and block lists.

I have and all I get is silence in response.

PS: If you are interested in feminist power analysis, silence is the response of the privileged when challenged. They don’t even have to acknowledge your argument or produce facts. Just silence. Maybe I should write a post: Twitter and Patterns of Privilege. What do you think?

August 3, 2018

Russian Bot Spotting, Magic Bullets, New York Times Tested

Filed under: Bots,Social Media,Twitter — Patrick Durusau @ 4:39 pm

How to Spot a Russian Bot by Daniel Costa-Roberts.

Spotting purported Russian bots on Twitter is a popular passtime for people unaware the “magic bullet” theory of communication has been proven to be false. One summary of “magic bullet” thinking:


The media (magic gun) fired the message directly into audience head without their own knowledge. The message cause the instant reaction from the audience mind without any hesitation is called “Magic Bullet Theory”. The media (needle) injects the message into audience mind and it cause changes in audience behavior and psyche towards the message. Audience are passive and they can’t resist the media message is called “Hypodermic Needle Theory”.

The “magic bullet” is an attractive theory for those selling advertising, but there is no scientific evidence to support it:


The magic bullet theory is based on assumption of human nature and it was not based on any empirical findings from research. Few media scholars do not accepting this model because it’s based on assumption rather than any scientific evidence. In 1938, Lazarsfeld and Herta Herzog testified the hypodermic needle theory in a radio broadcast “The War of the Worlds” (a famous comic program) by insert a news bulletin which made a widespread reaction and panic among the American Mass audience. Through this investigation he found the media messages may affect or may not affect audience.

“People’s Choice” a study conducted by Lazarsfeld in 1940 about Franklin D. Roosevelt election campaign and the effects of media messages. Through this study Lazarsfeld disproved the Magic Bullet theory and added audience are more influential in interpersonal than a media messages.

Nevertheless, MotherJones and Costa-Roberts outline five steps to spot a Russian bot:

  1. Hyperactivity – more than 50 or 60 tweets per day
  2. Suspicious images – stock avatar
  3. URL shorterners – use indicates a bot
  4. Multiple languages – polyglot indicates a bot
  5. Unlikely popularity – for given # of followers

OK, so let’s test those steps against a known non-Russian bot that favors the US government, the New York Times.

  1. Hyperactivity – New York Times joined Twitter, 2 March 2007, 4173 days, 328,555 tweets as of this afternoon, so, 78.73 on average per day. That’s hyperactive.
  2. Suspicious images – NYT symbol
  3. URL shorterners – Always – signals bot. (displays nytimes.com but if you check the links, URL shorterner)
  4. Multiple languages – Nope.
  5. Unlikely popularity – In which direction? NYT has 41,665,676 followers and only 17,145 likes, or one like for every 2340 followers.

On balance I would say the New York Times isn’t a Russian bot, but given it’s like to follower ratio, it needs to work on its social media posts.

Maybe the New York Times needs to hire a Russian bot farm?

March 11, 2018

Spreading “Fake News,” Science Says It Wasn’t Russian Bots

Filed under: Fake News,Politics,Twitter — Patrick Durusau @ 2:04 pm

The spread of true and false news online by Soroush Vosoughi, Deb Roy, and Sinan Aral. (Science 09 Mar 2018: Vol. 359, Issue 6380, pp. 1146-1151 DOI: 10.1126/science.aap9559)

Abstract:

We investigated the differential diffusion of all of the verified true and false news stories distributed on Twitter from 2006 to 2017. The data comprise ~126,000 stories tweeted by ~3 million people more than 4.5 million times. We classified news as true or false using information from six independent fact-checking organizations that exhibited 95 to 98% agreement on the classifications. Falsehood diffused significantly farther, faster, deeper, and more broadly than the truth in all categories of information, and the effects were more pronounced for false political news than for false news about terrorism, natural disasters, science, urban legends, or financial information. We found that false news was more novel than true news, which suggests that people were more likely to share novel information. Whereas false stories inspired fear, disgust, and surprise in replies, true stories inspired anticipation, sadness, joy, and trust. Contrary to conventional wisdom, robots accelerated the spread of true and false news at the same rate, implying that false news spreads more than the truth because humans, not robots, are more likely to spread it.

Real data science. The team had access to all the Twitter data and not a cherry-picked selection, which of course can’t be shared due to Twitter rules, or so say ISIS propaganda scholars.

The paper merits a slow read but highlights for the impatient:

  1. Don’t invest in bots or high-profile Twitter users for the 2018 mid-term elections.
  2. Craft messages with a high novelty factor that disfavor your candidates opponents.
  3. Your messages should inspire fear, disgust and surprise.

Democrats working hard to lose the 2018 mid-terms will cry you a river about issues, true facts, engagement on the issues and a host of other ideas used to explain losses to losers.

There’s still time to elect a progressive Congress in 2018.

Are you game?

February 14, 2018

Russian Influence! Russian Influence! Get Your Russian Influence Here!

Filed under: Journalism,News,Politics,Reporting,Twitter — Patrick Durusau @ 3:54 pm

Twitter deleted 200,000 Russian troll tweets. Read them here. by Ben Popken (NBC News)

From the post:

NBC News is publishing its database of more than 200,000 tweets that Twitter has tied to “malicious activity” from Russia-linked accounts during the 2016 U.S. presidential election.

These accounts, working in concert as part of large networks, pushed hundreds of thousands of inflammatory tweets, from fictitious tales of Democrats practicing witchcraft to hardline posts from users masquerading as Black Lives Matter activists. Investigators have traced the accounts to a Kremlin-linked propaganda outfit founded in 2013 known as the Internet Research Association (IRA). The organization has been assessed by the U.S. Intelligence Community to be part of a Russian state-run effort to influence the outcome of the 2016 U.S. presidential race. And they’re not done.

“There should be no doubt that Russia perceives its past efforts as successful and views the 2018 US midterm elections as a potential target for Russian influence operations,” Director of National Intelligence Dan Coats told the Senate Intelligence Committee Tuesday.

Wow!

What’s really amazing is that NBC keeps up the narrative of “Russian influence” while publishing data to the contrary!

No, I confess I haven’t read all 200K tweets but then neither has NBC, if they read any of them at all.

Download tweets.csv. (NBC link) (Don’t worry, I’ve stored a copy elsewhere should that one disappear.)

On Unix, try this: head -100 tweets.csv | awk -F "," '{ print $8 }' > 100-tweets.txt

The eight field of the csv file containing the text in each tweet.

Walk with me through the shadow of Russian influence and see how you feel:

  1. “RT @LibertyBritt: He’s the brilliant guy who shoots himself in the foot to spite his face. And tries to convince us to do it too. https:/…”
  2. “RT @K1erry: The Marco Rubio knockdown of Elizabeth Warren no liberal media outlet will cover https://t.co/Rh391fEXe3”
  3. “Obama on Trump winning: ‘Anything’s possible’ https://t.co/MjVMZ5TR8Y #politics”
  4. “RT @bgg2wl: Walmart
  5. “it’s impossible! #TexasJihad”
  6. “RT @LibsNoFun: Who will wave the flag? #DayWithoutImmigrants https://t.co/Cn6JKqzE6X”
  7. “Bewaffnete attackieren Bus mit koptischen Christen #Islamisten #ISIS
  8. “”
  9. “The bright example of our failing education https://t.co/DgboGgkgVj”
  10. “@sendavidperdue How are they gonna protect us if they just let a bunch of terrorist walk the cities of our city? #StopIslam #IslamKills”

Only ten “Russian influence” tweets and I’m already thinking about vodka. You?

Let’s try another ten:

  1. “FC Barcelonas youth academy! La Masia doin work! Double tap for these little guys! https://t.co/eo1qIvLjgS”
  2. “When I remember it’s #Friyay https://t.co/yjBTsaFaR2”
  3. “RT @Ladydiann2: Remove these Anti Americans from America enough is enough abuse American freedoms how dare you low lives https://t.co/G44E6…”
  4. “RT @BreitbartNews: This week’s “”Sweden incident.”” https://t.co/EINMeA9R2T”
  5. “RT @alisajoy331: Prayer sent Never stop fighting💔 https://t.co/B9Tno5REjm”
  6. “RT @RossMoorhouse: #ItsRiskyTo
  7. “”
  8. “RT @RedState: The KKK Says A&E Producers Tried to Stage Fake Scenes for Cancelled Documentary https://t.co/HwaebG2rdI”
  9. “RT @hldb73: Bryan or Ryan Adams #whenthestarsgoblue #RejectedDebateTopics @WorldOfHashtags @TheRyanAdams @bryanadams https://t.co/wFBdne8K…”
  10. “RT @WorldTruthTV: #mutual #respect https://t.co/auIjJ2RdBU”

Well comrade. Do you feel any different about the motherland? I don’t. Let’s read some more of her tweets!

  1. “tired of kids how to get rid #SearchesGoogleIsAshamedOf”
  2. “RT @crookedwren: “”Praise be to the Lord
  3. “RT @deepscreenshots: https://t.co/1IuHuiAIJB”
  4. “Kareem Abdul Jabber #OneLetterOffSports @midnight #HashtagWars”
  5. “#God can be realized through all paths. All #religions…”
  6. “RT @RawStory: ‘Star Wars’ Han Solo movie to begin production in January https://t.co/bkZq7F7IkD”
  7. “RT @KStreetHipster: Hamner-Brown is already on its way here. It’s been on it’s way for billions of years. #KSHBC https://t.co/TQh86xN3pJ”
  8. “RT @TrumpSuperPAC: Obama’s a Muslim & this video from @FoxNews proves it! Even @CNN admits Obama’s training protesters/jihadists! #MAGA htt…”
  9. “RT @schotziejlk: .@greta Who is your #SuperBowl favorite?”
  10. “RT @LefLaneLivin: @trueblackpower As Black People we need to Support

I’m going to change my middle name to Putin out of respect for our glorious leader!

Is it respectful to get a Putin tatoo on your hiney?

(Recovers from Russian influence)

This is NBC’s damning proof of Russian influence. Like I said at the beginning, Wow!

As in Wow! how dumb.

OK, to be fair, any tweet set will have a lot of trash in it and grepping for Clinton/clinton and Trump/trump returns 20,893 for Clinton and 49,669 for Trump.

I haven’t checked but liberals talking about Clinton/Trump pre-election ran about 2 1/2 times more mentions of Trump than Clinton. (Odd way to run a campaign.)

So, the usual grep/head, etc. and the first ten “Clinton” tweets are:

  1. “Clinton: Trump should’ve apologized more
  2. “RT @thomassfl: Wikileaks E-Mails:  Hillary Clinton Blackmailed Bernie Sanders https://t.co/l9X32FegV6.”
  3. “Clinton’s VP Choice: More Harm Than Good https://t.co/iGnLChFHeP”
  4. “Hillary Clinton vows to fight
  5. “RT @Rammer_Jammer84: I don’t know about Hilary Clinton having a body double but it’s super weird that she came out by herself considering s…”
  6. “RT @Darren32895836: After Hillary Clinton Caught 4attempting 2take advantage of Americans hardships &tears changes Strat #PrayForFlorida ht…”
  7. “RT @steph93065: Hillary Clinton: Donald Trump’s Veterans Press Conference ‘Disgraceful’ – Breitbart https://t.co/CVvBOrTJBX”
  8. “RT @DianeRainie1: Hey @HillaryClinton this message is for you. Pack it up & go home Hillary
  9. “”
  10. “”RejectedDebateTopics””

and the first ten “Trump” tweets are:

  1. “Clinton: Trump should’ve apologized more
  2. “RT @AriaWilsonGOP: 3 Women Face Charges After Being Caught Stealing Dozens Of Trump Signs https://t.co/JjlZxaW3JN https://t.co/qW2Ok9ROxH”
  3. “RT @America_1st_: CW: “”The thing that impressed me was that Trump is always comfortable in own skin
  4. “Dave Chappelle: “”Black Lives Matter”” is the worst slogan I’ve ever heard! How about “”enough is enough””? VotingTrump! https://t.co/5okvmoQhcj”
  5. “Obama on Trump winning: ‘Anything’s possible’ https://t.co/MjVMZ5TR8Y #politics”
  6. “RT @TrumpSuperPAC: Obama’s a Muslim & this video from @FoxNews proves it! Even @CNN admits Obama’s training protesters/jihadists! #MAGA htt…”
  7. “Deceitful Media caught on act when trying to drive the “”Donald Trump is racist”” rhetoric.
  8. “”
  9. “RT @Veteran4Trump: A picture you will never see on @CNN or @MSNBC #BlacksForTrump Thumbs up for Trump 👍#MakeAmericaGreatAgain #Blacks4Trump…”
  10. “RT @steph93065: Hillary Clinton: Donald Trump’s Veterans Press Conference ‘Disgraceful’ – Breitbart https://t.co/CVvBOrTJBX”

That’s a small part of NBC’s smoking gun on Russian influence?

Does it stand to reason that the CIA, NSA, etc., have similar cap-gun evidence?

Several options present themselves:

  • Intelligence operatives and their leaders have been caught lying, again. That is spinning tales any reasonable reading of the evidence doesn’t support.
  • Intelligence operatives are believing one more impossible thing before breakfast and ignoring the evidence.
  • Journalists have chosen to not investigate whether intelligence operatives are lying or believing impossible things and report/defend intelligence conclusions.

Perhaps all three?

In any event, before crediting any “Russian influence” story, do take the time to review at least some of the 200,000 pieces of “evidence” NBC has collected on that topic.

You will be left amazed that you ever believed NBC News on any topic.

January 6, 2018

21 Recipes for Mining Twitter Data with rtweet

Filed under: R,Social Media,Tweets,Twitter — Patrick Durusau @ 5:26 pm

21 Recipes for Mining Twitter Data with rtweet by Bob Rudis.

From the preface:

I’m using this as way to familiarize myself with bookdown so I don’t make as many mistakes with my web scraping field guide book.

It’s based on Matthew R. Russell’s book. That book is out of distribution and much of the content is in Matthew’s “Mining the Social Web” book. There will be many similarities between his “21 Recipes” book and this book on purpose. I am not claiming originality in this work, just making an R-centric version of the cookbook.

As he states in his tome, “this intentionally terse recipe collection provides you with 21 easily adaptable Twitter mining recipes”.

Rudis has posted about this editing project at: A bookdown “Hello World” : Twenty-one (minus two) Recipes for Mining Twitter with rtweet, which you should consult if you want to contribute to this project.

Working through 21 Recipes for Mining Twitter Data with rtweet will give you experience proofing a text and if you type in the examples (no cut-n-paste), you’ll develop rtweet muscle memory.

Enjoy!

December 28, 2017

Twitter Taking Sides – Censorship-Wise

Filed under: Censorship,Free Speech,Twitter — Patrick Durusau @ 10:16 pm

@wikileaks pointed out that Twitter’s censorship policies are taking sides:

Accounts that affiliate with organizations that use or promote violence against civilians to further their causes. Groups included in this policy will be those that identify as such or engage in activity — both on and off the platform — that promotes violence. This policy does not apply to military or government entities and we will consider exceptions for groups that are currently engaging in (or have engaged in) peaceful resolution.
… (emphasis added)

Does Twitter need a new logo? Birds with government insignia dropping bombs on civilians?

December 14, 2017

Twitter Bot Template – If You Can Avoid Twitter Censors

Filed under: Bots,Python,Twitter — Patrick Durusau @ 11:04 am

Twitter Bot Template

From the webpage:

Boilerplate for creating simple, non-interactive twitter bots that post periodically. My comparisons bot, @botaphor, is an example of how I use this template in practice.

This is intended for coders familiar with Python and bash.

If you can avoid Twitter censors (new rules, erratically enforced, a regular “feature”), then this Twitter bot template may interest you.

Make tweet filtering a commercial opportunity and Twitter can drop the cost with no profit center of tweet censorship.

Unlikely because policing other people is such a power turn-on.

Still, this is the season for wishes.

December 5, 2017

Name a bitch badder than Taylor Swift

Filed under: Feminism,R,Twitter — Patrick Durusau @ 4:27 pm

It all began innocently enough, a tweet with this image and title by Nutella.

Maëlle Salmon reports in Names of b…..s badder than Taylor Swift, a class in women’s studies? that her first pass on tweets quoting Nutella’s tweet, netted 15,653 tweets! (Salmon posted on 05 December 2017 so a later tweet count will be higher.)

Salmon uses rtweet to obtain the tweets, cleanNLP to extract entities, and then enhances those entities with Wikidata.

There’s a lot going on in this one post!

Enjoy the post and remember to follow Maëlle Salmon on Twitter!

Other value-adds for this data set?

October 10, 2017

Busting Fake Tweeters

Filed under: Journalism,News,Reporting,Twitter — Patrick Durusau @ 6:36 pm

The ultimate guide to bust fake tweeters: A video toolkit in 10 steps by Henk van Ess.

From the post:

Twitter is full of false information. Even Twitter co-founder Ev Williams recognizes that there is a “junk information epidemic going on,” as “[ad-driven platforms] are benefiting from people generating attention at pretty much any cost.”

This video toolkit is intended to help you debunk dubious tweets. It was first developed in research by the Institute for Strategic Dialogue and the Arena Program at the London School of Economics to detect Russian social media influence during the German elections. It was also the basis for a related BuzzFeed article on a Russian bot farm and tweets about the AfD  — the far-right party that will enter the German parliament for the first time.

This is an excellence resource for teaching users skepticism about Twitter accounts.

For your use in creating a personal cheatsheet (read van Ess for the links):

  1. Find the exact minute of birth
  2. Find the first words
  3. Check the followers
  4. Find Twitter users in Facebook
  5. Find suspicious words in tweets
  6. Searching in big data
  7. Connect a made up Twitter handle to a real social media account
  8. Find a social score
  9. How alive is the bot?
  10. When (and how) is your bot tweeting?

Deciding that a Twitter account maybe a legitimate is only the first step in evaluating tweeted content.

The @WSJ account belongs to the Wall Street Journal, but it doesn’t follow their tweets are accurate or even true. Witness their repetition of government rumors about Kerpersky Lab for example. Not one shred of evidence, but WSJ repeats it.

Be skeptical of all Tweets, not just ones attributed to the “enemy of the day.”

September 27, 2017

Salvation for the Left Behind on Twitter’s 280 Character Limit

Filed under: Social Media,Twitter — Patrick Durusau @ 3:14 pm

If you are one of the “left behind” on Twitter’s expansion to a 280 character limit, don’t despair!

Robert Graham (@ErrataRob) rides to your rescue with: Browser hacking for 280 character tweets.

Well, truth is Bob covers more than simply reaching the new 280 character limit for the left behind, covering HTTP requests, introduces Chrome’s DevTool, command line use of cURL.

Take a few minutes to walk through Bob’s post.

A little knowledge of browsers and tools will put you far ahead of your management.

September 24, 2017

Women in Data Science (~1200) – Potential Speaker List

Filed under: Data Science,Twitter — Patrick Durusau @ 3:49 pm

When I last posted about Data Science Renee‘s twitter list of women in data science in had ~632 members.

That was in April of 2016.

As of today, the list has 1,203 members! By the time you look, that number will be different again.

I call this a “potential speaker list” because not every member may be interested in your conference or have the time to attend.

Have you made a serious effort to recruit women speakers if you have not consulted this list and others like it?

Serious question.

Do you have a serious answer?

July 15, 2017

Twitter – Government Censor’s Friend

Filed under: Censorship,Free Speech,Twitter — Patrick Durusau @ 3:59 pm

Governments, democratic, non-democratic, kingships, etc. that keep secrets from the public, share a common enemy in Wikileaks.

Wikileaks self-describes in part as:

WikiLeaks is a multi-national media organization and associated library. It was founded by its publisher Julian Assange in 2006.

WikiLeaks specializes in the analysis and publication of large datasets of censored or otherwise restricted official materials involving war, spying and corruption. It has so far published more than 10 million documents and associated analyses.

“WikiLeaks is a giant library of the world’s most persecuted documents. We give asylum to these documents, we analyze them, we promote them and we obtain more.” – Julian Assange, Der Spiegel Interview.

WikiLeaks has contractual relationships and secure communications paths to more than 100 major media organizations from around the world. This gives WikiLeaks sources negotiating power, impact and technical protections that would otherwise be difficult or impossible to achieve.

Although no organization can hope to have a perfect record forever, thus far WikiLeaks has a perfect in document authentication and resistance to all censorship attempts.

Those same governments, share a common ally in Twitter, which has engaged in systematic actions to diminish the presence/influence of Julian Assange on Twitter.

Caitlin Johnstone documents Twitter’s intentional campaign against Assange in Twitter Is Using Account Verification To Stifle Leaks And Promote War Propaganda.

Catch Johnstone’s post for the details but then:

  1. Follow @JulianAssange on Twitter (watch for minor variations that are not this account.
  2. Tweet to your followers, at least once a week, urging them to follow @JulianAssange
  3. Investigate and support non-censoring alternatives to Twitter.

You can verify Twitter’s dilution of Julian Assange for yourself.

Type “JulianAssange_” in the Twitter search box (my results):

Twitter was a remarkably good idea, but has long since poisoned itself with censorship and pettiness.

Your suggested alternative?

May 26, 2017

Thank You, Scott – SNL

Filed under: Facebook,Social Media,Twitter — Patrick Durusau @ 8:49 pm

I posted this to Facebook, search for “Thanks Scott SNL” to find my post or that of others.

Included this note (with edits):

Appropriate social media warriors (myself included). From sexism and racism to fracking and pipelines, push back in the real world if you [want] change. Push back on social media for a warm but meaningless feeling of solidarity.

For me the “real world,” includes cyberspace, where pushing can have consequences.

You?

April 5, 2017

Mastodon (Tor Access Recommended)

Filed under: Social Media,Twitter — Patrick Durusau @ 8:00 pm

Mastodon

From the homepage:

Mastodon is a free, open-source social network. A decentralized alternative to commercial platforms, it avoids the risks of a single company monopolizing your communication. Pick a server that you trust — whichever you choose, you can interact with everyone else. Anyone can run their own Mastodon instance and participate in the social network seamlessly.

What sets Mastodon apart:

  • Timelines are chronological
  • Public timelines
  • 500 characters per post
  • GIFV sets and short videos
  • Granular, per-post privacy settings
  • Rich block and muting tools
  • Ethical design: no ads, no tracking
  • Open API for apps and services

… (emphasis in original)

No regex for filtering posts but it does have:

  • Block notifications from non-followers
  • Block notifications from people you don’t follow

One or both should cover most of the harassment cases.

I was surprised by the “Pick a server that you trust…” suggestion.

Really? A remote server being run by someone unknown to me? Bad enough that I have to “trust” my ISP, to a degree, but an unknown?

You really need a Tor based email account and use Tor for access to Mastodon. Seriously.

March 26, 2017

Politics For Your Twitter Feed

Filed under: Government,Politics,Tweets,Twitter — Patrick Durusau @ 8:28 am

Hungry for more political tweets?

GovTrack created the Members of Congress Twitter list.

Barometer of congressional mood?

Enjoy!

March 10, 2017

Creating A Social Media ‘Botnet’ To Skew A Debate

Filed under: Education,Government,Politics,Social Media,Twitter — Patrick Durusau @ 5:34 pm

New Research Shows How Common Core Critics Built Social Media ‘Botnets’ to Skew the Education Debate by Kevin Mahnken.

From the post:

Anyone following education news on Twitter between 2013 and 2016 would have been hard-pressed to ignore the gradual curdling of Americans’ attitudes toward the Common Core State Standards. Once seen as an innocuous effort to lift performance in classrooms, they slowly came to be denounced as “Dirty Commie agenda trash” and a “Liberal/Islam indoctrination curriculum.”

After years of social media attacks, the damage is impressive to behold: In 2013, 83 percent of respondents in Education Next’s annual poll of Americans’ education attitudes felt favorably about the Common Core, including 82 percent of Republicans. But by the summer of 2016, support had eroded, with those numbers measuring only 50 percent and 39 percent, respectively. The uproar reached such heights, and so quickly, that it seemed to reflect a spontaneous populist rebellion against the most visible education reform in a decade.

Not so, say researchers with the University of Pennsylvania’s Consortium for Policy Research in Education. Last week, they released the #commoncore project, a study that suggests that public animosity toward Common Core was manipulated — and exaggerated — by organized online communities using cutting-edge social media strategies.

As the project’s authors write, the effect of these strategies was “the illusion of a vociferous Twitter conversation waged by a spontaneous mass of disconnected peers, whereas in actuality the peers are the unified proxy voice of a single viewpoint.”

Translation: A small circle of Common Core critics were able to create and then conduct their own echo chambers, skewing the Twitter debate in the process.

The most successful of these coordinated campaigns originated with the Patriot Journalist Network, a for-profit group that can be tied to almost one-quarter of all Twitter activity around the issue; on certain days, its PJNET hashtag has appeared in 69 percent of Common Core–related tweets.

The team of authors tracked nearly a million tweets sent during four half-year spans between September 2013 and April 2016, studying both how the online conversation about the standards grew (more than 50 percent between the first phase, September 2013 through February 2014, and the third, May 2015 through October 2015) and how its interlocutors changed over time.

Mahnken talks as though creating a ‘botnet’ to defeat adoption of the Common Core State Standards is a bad thing.

I never cared for #commoncore because testing makes money for large and small testing vendors. It has no other demonstrated impact on the educational process.

Let’s assume you want to build a championship high school baseball team. To do that, various officious intermeddlers, who have no experience with baseball, fund creation of the Common Core Baseball Standards.

Every three years, every child is tested against the Common Core Baseball Standards and their performance recorded. No funds are allocated for additional training for gifted performers, equipment, baseball fields, etc.

By the time these students reach high school, will you have the basis for a championship team? Perhaps, but if you do, it due to random chance and not the Common Core Baseball Standards.

If you want a championship high school baseball team, you fund training, equipment, baseball fields and equipment, in addition to spending money on the best facilities for your hoped for championship high school team. Consistently and over time you spend money.

The key to better education results isn’t testing, but funding based on the education results you hope to achieve.

I do commend the #commoncore project website for being an impressive presentation of Twitter data, even though it is clearly a propaganda machine for pro Common Core advocates.

The challenge here is to work backwards from what was observed by the project to both principles and tactics that made #stopcommoncore so successful. That is we know it has succeeded, at least to some degree, but how do we replicate that success on other issues?

Replication is how science demonstrates the reliability of a technique.

Looking forward to hearing your thoughts, suggestions, etc.

Enjoy!

March 6, 2017

Continuing Management Fail At Twitter

Filed under: Censorship,Free Speech,Twitter — Patrick Durusau @ 11:54 am

Twitter management continues to fail.

Consider censoring the account of Lauri Love. (a rumored hacker)

Competent management at Twitter would be licensing the rights to create shareable mutes/filters for all posts from Lauri Love.

The FBI, Breitbart, US State Department, and others would vie for users of their filters, which block “dangerous and/or seditious content.”

Filters licensed in increments, depending on how many shares you want to enable.

Twitter with no censorship at all would drive the market for such filters.

Licensing filters by number of shares provides a steady revenue stream and Twitter could its censorship prone barnacles. More profit, reduced costs, what’s not to like?

PS: I ask nothing for this suggestion. Getting Twitter out of the censorship game on behalf of governments is benefit enough for me.

March 4, 2017

Trump Tweets Strategically – You Respond (fill in the blank)

Filed under: Politics,Tweets,Twitter — Patrick Durusau @ 4:00 pm

George Lakoff tweeted:

Here’s an example of a “strategic” tweet by Trump.

Donald J. Trump tweets:

Terrible! Just found out that Obama had my “wires tapped” in Trump Tower just before the victory. Nothing found. This is McCarthyism!

For testing purposes, how would you characterize this sample of tweets that are a small part of the 35K replies to Trump’s tweet.


pourmecoffee‏Verified account @pourmecoffee
@realDonaldTrump Correct. Making allegations without evidence is the literal definition of McCarthyism.

FFT-Obama for Prison‏ @FemalesForTrump
.@pourmecoffee
when will the liars learn. Trump ALWAYS does his homework! The truth will support his tweet in 3, 2, 1 …
#saturdaymorning

Ignatz‏ @ignatzz
@FemalesForTrump @pourmecoffee Yes, I remember that proof that Obama was born in Kenya. And the Bowling Green Massacre.

FFT-Obama for Prison‏ @FemalesForTrump
@ignatzz @pourmecoffee he WAS born in Kenya. Hawaii b/c is a fake. #fact
He didn’t make the bowling green statement. Now go away

Lisa Armstrong‏Verified account @LisaArmstrong
@FemalesForTrump You people are still stuck on the lie that Obama was born in Kenya? Why? Where is the proof? #alternativefacts

Jet Black‏ @jetd69
@LisaArmstrong @FemalesForTrump There’s little point in arguing with her. She’s as off her chops as he is. Females for Trump indeed!

Lisa Armstrong‏Verified account @LisaArmstrong
@jetd69 @FemalesForTrump I know you’re right. It’s just that the willingness of #Trump supporters to believe flat out lies astounds me.

AngieStrader‏ @AngieStrader
@LisaArmstrong @jetd69 @FemalesForTrump this goes both ways. Dems want Trump on treason. Based on what facts? What verifiable sources?

Lisa Armstrong‏Verified account @LisaArmstrong
@AngieStrader The difference is there’s a long list of shady things Trump has actually done. These are facts. Obama being Kenyan is a lie.

Do you see any strategic tweets in that list or in the other 37K responses (as of Saturday afternoon, 4 March 2017)?

If the point of Trump’s tweet was diversion, I would have to say it succeeded beautifully.

You?

The strategic response to a Trump tweet is ignoring them in favor of propagating your theme.

February 17, 2017

Twitter reduces reach of users it believes are abusive [More Opaque Censorship]

Filed under: Censorship,Free Speech,Twitter — Patrick Durusau @ 11:25 am

Twitter reduces reach of users it believes are abusive

More opaque censorship from Twitter:

Twitter has begun temporarily decreasing the reach of tweets from users it believes are engaging in abusive behaviour.

The new action prevents tweets from users Twitter has identified as being abusive from being displayed to people who do not follow them for 12 hours, thus reducing the user’s reach.

If the user were to mention someone who does not follow them on the social media site, that person would not see the tweet in their notifications. Again, this would last for 12 hours.

If the user who had posted abusive tweets was retweeted by someone else, this tweet would not be able to be seen by people who do not follow them, again reducing their Twitter reach.
… (emphasis in original)

I’m assuming this is one of the changes Ed Ho alluded to in An Update on Safety (February 7, 2017) when he said:

Collapsing potentially abusive or low-quality Tweets:

Our team has also been working on identifying and collapsing potentially abusive and low-quality replies so the most relevant conversations are brought forward. These Tweet replies will still be accessible to those who seek them out. You can expect to see this change rolling out in the coming weeks.
… (emphasis in original)

No announcements for:

  • Grounds for being deemed “abusive.”
  • Process for contesting designation as “abusive.”

Twitter is practicing censorship, the basis for which is opaque and the censored have no impartial public forum for contesting that censorship.

In the interest of space, I forego the obvious historical comparisons.

All of which could have been avoided by granting Twitter users:

The ability to create and share filters for tweets.

Even a crude filtering mechanism should enable me to filter tweets that contain my Twitter handle, but that don’t originate from anyone I follow.

So Ed Ho, why aren’t users being empowered to filter their own streams?

February 9, 2017

Republican Regime Creates New Cyber Market – Burner Twitter/Facebook Accounts

Filed under: Facebook,Government,Security,Twitter — Patrick Durusau @ 4:17 pm

The current Republican regime has embarked upon creating a new cyber market, less than a month after taking office.

Samatha Dean (Tech Times) reports:

Planning a visit to the U.S.? Your passport is not the only thing you may have to turn in at the immigration counter, be prepared to relinquish your social media account passwords as well to the border security agents.

That’s right! According to a new protocol from the Homeland Security that is under consideration, visitors to the U.S. may have to give their Twitter and Facebook passwords to the border security agents.

The news comes close on the heels of the Trump administration issuing the immigration ban, which resulted in a massive state of confusion at airports, where several people were debarred from entering the country.

John F. Kelly, the Homeland Security Secretary, shared with the Congress on Feb. 7 that the Trump administration was considering this option. The measure was being weighed as a means to sieve visa applications and sift through refugees from the Muslim majority countries that are under the 90-day immigration ban.

I say burner Twitter/Facebook accounts, if you plan on making a second trip to the US, you will need to have the burner accounts maintained over the years.

The need for burner Twitter/Facebook accounts, ones you can freely disclose to border security agents, presents a wide range of data science issues.

In no particular order:

  • Defeating Twitter/Facebook security on a large scale. Not trivial but not the hard part either
  • Creating accounts with the most common names
  • Automated posting to accounts in their native language
  • Posts must be indistinguishable from human user postings, i.e., no auto-retweets of Sean Spicer
  • Profile of tweets/posts shows consistent usage

I haven’t thought about burner bank account details before but that certainly should be doable. Especially if you have a set of banks on the Net that don’t have much overhead but exist to keep records one to the other.

Burner bank accounts could be useful to more than just travelers to the United States.

Kudos to the new Republican regime and their market creation efforts!

January 26, 2017

Twistance – “Rogue” Twitter Accounts – US Federal Science Agencies

Filed under: Government,Science,Twitter — Patrick Durusau @ 2:07 pm

Alice Stollmeyer has put together Twistance:

Twitter + resistance = #Twistance. “Rogue” Twitter accounts from US federal science agencies.

As of 26 January 2017, 44 members and 5,133 subscribers.

A long overdue step towards free speech for government employees and voters making decisions on what is known inside the federal government.

Caution:

A claim to be an “alternative” account may or may not be true. As with the official accounts, evaluate factual claims for yourself. Use good security practices when communicating with unknown accounts. (Some of the account names are very close in spelling but are separate accounts.)

  • Alt Hi Volcanoes NP The Unofficial “Resistance” team of Hawaii Volcanoes National Park. Not taxpayer funded.
  • Alt HHS Unofficial and unaffiliated resistance account by concerned scientists for humanity.
  • The Alt NPS and EPA Real news regarding the NPS, EPA, climate science and environmentalism
  • Alt Science Raising awareness of climate change and other threats posed by science denial. Not affiliated with the US gov. #Resist
  • Alternative CDC Unofficial unaffiliated resistance account by concerned scientists for humanity.
  • Alternative HeHo A parody account for the Herbert Hoover National Historic Site
  • Alternative NIH Unofficial group of science advocates. Stand up for science, rights, equality, social justice, & ultimately, for the health of humanity.
  • Alternative NOAA The Unofficial “Resistance” team of the NOAA. Account not tax payer subsidized. We study the oceans, and the atmosphere to understand our planet. #MASA
  • AltBadlandsNatPark You’ll never shut us down, Drumpf!
  • Alt-Badlands NPS Bigly fake #badlandsnationalpark. ‘Sad!’ – Donald J Trump. #badlands #climate #science #datarefuge #resist #resistance
  • AltEPA He can take our official Twitter but he’ll never take our FREEDOM. UNOFFICIALLY resisting.
  • altEPA The Unofficial “Resistance” team of U.S. Environmental Protection Agency. Not taxpayer subsidised! Environmental conditions may vary from alternative facts.
  • AltFDA Uncensored FDA
  • AltGlacierNPS The unofficial Twitter site for Glacier National Park of Science Fact.
  • AltHot Springs NP The Resistance Account of America’s First Resort and Preserve. Account Run By Friends of HSNP.
  • AltLassenVolcanicNP The Unofficial “Resistance” team. Within peaceful mountain forests you will find hissing fumaroles and boiling mud pots and people ready to fight for science.
  • AltMountRainierNPS Unofficial “Resistance” Team from the Mount Rainier National Park Service. Protecting what’s important..
  • AltNASA The unofficial #resist team of the National Aeronautics and Space Administration.
  • AltOlympicNPS Unofficial resistance team of the Olympic National Park. protecting what’s important and fighting fascism with science.
  • AltRockyNPS Unofficial account that is being held for people associated with RMNP. DM if you might be interested in it.
  • AltUSARC USARC’s main duties are to develop an integrated national Arctic research policy and to assist in establishing an Arctic research plan to implement it.
  • AltUSDA Resisting the censorship of facts and science. Truth wins in the end.
  • AltUSForestService The unofficial, and unsanctioned, “Resistance” team for the U.S. Forest Service. Not an official Forest Service account, not publicly funded, citizen run.
  • AltUSFWS The Alt U.S. Fish Wildlife Service (AltUSFWS) is dedicated to the conservation, protection and enhancement of fish, wildlife and plants and their habitats
  • AltUSFWSRefuge The Alt U.S. Fish Wildlife Service (AltUSFWSRefuge) is dedicated to the conservation, protection and enhancement of fish, wildlife and plants and their habitats
  • ALTUSNatParkSer The Unofficial team of U.S. National Park Service. Not taxpayer subsidised! Come for rugged scenery, fossil beds, 89 million acres of landscape
  • AltUSNatParkService The Unofficial #Resistance team of U.S. National Park Service. Not taxpayer subsidised! Come for rugged scenery, facts & 89 million acres of landscape #climate
  • AltNWS The Unofficial Resistance team of U.S. National Weather Service. Not taxpayer subsidized! Come for non-partisan science-based weather, water, and climate info.
  • AltYellowstoneNatPar We are a group of employees and scientists in Yellowstone national park. We are here to continue providing the public with important information
  • AltYosemiteNPS “Unofficial” Resistance Team. Reporting facts & protecting what’s important!
  • Angry National Park Preserving the ecological and historical integrity of National Parks while also making them available and accessible for public use and enjoyment dammit all.
  • BadHombreLands NPS Unofficial feed of Badlands NP. Protecting rugged scenery, fossil beds, 244,000 acres of mixed-grass prairie & wildlife from two-bit cheetoh-hued despots.
  • BadlandsNPSFans Shmofficial fake feed of South Dakota’s Badlands National Park (Great Again™ Edition) Account not run by park employees, current or former, so leave them alone.
  • GlacierNPS The alternative Twitter site for Glacier National Park.
  • March for Science Planning a March for Science. Date TBD. We’ll let you know when official merchandise is out to cover march costs.
  • NOAA (uncensored)
  • Resistance_NASA We are a #Resist sect of the National Aeronautics and Space Administration.
  • Rogue NASA The unofficial “Resistance” team of NASA. Not an official NASA account. Not managed by gov’t employees. Come for the facts, stay for the snark.
  • NatlParksUnderground We post the information Donald Trump censors #FindYourPark #NPS100
  • NWS Podunk We’re the third wheel of forecast offices. We still use WSR-57. Winner of Biggest Polygon at the county fair. Not an actual NWS office…but we should be.
  • Rogue NOAA Research on our climate, oceans, and marine resources should be subject to peer [not political] review. *Not an official NOAA account*
  • Stuff EPA Would Say We post info that Donald Trump censors. We report what the U.S. Environmental Protection Agency would say. Chime in w/ #StuffEPAWouldSay
  • U.S. EPA – Ungagged Ungagged news, links, tips, and conversation that the U.S. Environmental Protection Agency is unable to tell you. Not directly affiliated with @EPA.
  • U.S. Science Service Uncensored & unofficial tweets re: the science happening at the @EPA, @USDA, @NatParkService, @NASA, @NOAA etc. #ClimateChangeIsReal #DefendScience

January 19, 2017

Why I Tweet by Donald Trump

Filed under: Journalism,News,Reporting,Twitter — Patrick Durusau @ 8:02 pm

David Uberti and Pete Vernon in The coming storm for journalism under Trump capture why Donald Trump tweets:


As Trump explained the retention of his personal Twitter handle to the Sunday Times recently: “I thought I’d do less of it, but I’m covered so dishonestly by the press—so dishonestly—that I can put out Twitter…I can go bing bing bing and I just keep going and they put it on and as soon as I tweet it out—this morning on television, Fox: Donald Trump, we have breaking news.

In order for Trump tweets to become news, two things are required:

  1. Trump tweets (quite common)
  2. Media evaluates the tweets to be newsworthy (should be less common)

Reported as newsworthy tweets are unlikely to match the sheer volume of Trump’s tweeting.

You have all read:

trump-on-sat-night-460

Is Trump’s opinion, to which he is entitled, about Saturday Night Live newsworthy?

Trump on television is as trustworthy as the “semi-literate one-legged man” Dickens quoted for the title “Our Mutual Friend” is on English grammar. (Modern American Usage by William Follett, edited by Jacques Barzum. Under the entry for “mutual friend.”)

Other examples abound but suffice it to say the media needs to make its own judgments about newsworthy or not.

Otherwise the natters of another semi-literate become news by default for the next four years.

January 6, 2017

Online Database of “Verified” Twitter Accounts (Right On!)

Filed under: Twitter,Wikileaks — Patrick Durusau @ 4:12 pm

The WikiLeaks Task Force tweeted on 6 Jan. 2017:

We are thinking of making an online database with all “verified” twitter accounts & their family/job/financial/housing relationships.

There are a number of comments to this tweet, the ones containing “dox,” “doxx,” “doxing,” “creepy,” “evil,” etc. that should be ignored.

Ignored because intelligence agencies, news organizations, merchants, banks, etc. are all collecting and organizing that data and more.

Ignored because the public should not preemptively disarm itself.

If anything, the Wikileaks Task Force should start with “verified” Twitter accounts and expand outwards, rapidly.

The public should be able to rapidly find relationships of individuals nominated for office, who contribute money to candidates, who profit from contracts, who launder public money. The public should have the same advantages intelligence agencies enjoy today.

To the nay-sayers to the WikiLeaks Task Force proposal:

Why do you seek to prevent putting the public on a better footing vis-a-vis government?

Question to my readers: What do the nay-sayers gain from a disarmed public?

Three More Reasons To Learn R

Filed under: Facebook,Programming,R,Statistics,Twitter — Patrick Durusau @ 3:31 pm

Three reasons to learn R today by David Smith.

From the post:

If you're just getting started with data science, the Sharp Sight Labs blog argues that R is the best data science language to learn today.

The blog post gives several detailed reasons, but the main arguments are:

  1. R is an extremely popular (arguably the most popular) data progamming language, and ranks highly in several popularity surveys.
  2. Learning R is a great way of learning data science, with many R-based books and resources for probability, frequentist and Bayesian statistics, data visualization, machine learning and more.
  3. Python is another excellent language for data science, but with R it's easier to learn the foundations.

Once you've learned the basics, Sharp Sight also argues that R is also a great data science to master, even though it's an old langauge compared to some of the newer alternatives. Every tool has a shelf life, but R isn't going anywhere and learning R gives you a foundation beyond the language itself.

If you want to get started with R, Sharp Sight labs offers a data science crash course. You might also want to check out the Introduction to R for Data Science course on EdX.

Sharp Sight Labs: Why R is the best data science language to learn today, and Why you should master R (even if it might eventually become obsolete)

If you need more reasons to learn R:

  • Unlike Facebook, R isn’t a sinkhole of non-testable propositions.
  • Unlike Instagram, R is rarely NSFW.
  • Unlike Twitter, R is a marketable skill.

Glad to hear you are learning R!

December 21, 2016

Mining Twitter Data with Python [Trump Years Ahead]

Filed under: Data Mining,Python,Twitter — Patrick Durusau @ 5:24 pm

Marco Bonzanini, author of Mastering Social Media Mining with Python, has a seven part series of posts on mining Twitter with Python.

If you haven’t been mining Twitter before now, President-elect Donald Trump is about to change all that.

What if Trump continues to tweet as President and authorizes his appointees to do the same? Spontaneity isn’t the same thing as openness but it could prove to be interesting.

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