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

December 19, 2016

Auto Trump fact-checks – Alternative to Twitter Censorship

Filed under: News,Reporting,Tweets,Twitter — Patrick Durusau @ 9:27 pm

Washington Post automatically inserts Trump fact-checks into Twitter by Sam Machkovech.

From the post:

In an apparent first for any American news outlet, the Washington Post released a Chrome plug-in on Friday designed to fact-check posts from a single Twitter account. Can you guess which one?

The new “RealDonaldContext” plug-in for the Google Chrome browser, released by WaPo reporter Philip Bump, adds fact-check summaries to selected posts by President-elect Donald Trump. Users will need to click a post in The Donald’s Twitter feed to see any fact-check information from the Washington Post, which appears as a gray text box beneath the tweet.

I differ with the Washington Post on its slavish reporting of unsubstantiated claims of the US intelligence community, but high marks for the “RealDonaldContext” plug-in for the Google Chrome browser!

What a great alternative to censoring “fake news” on Twitter! Fact check it!

Pointers to source code for similar plug-ins?

December 13, 2016

The Twitterverse of Donald Trump, in 26,234 Tweets

Filed under: Politics,Tweets,Twitter — Patrick Durusau @ 7:35 pm

The Twitterverse of Donald Trump, in 26,234 Tweets by Lam Thuy Vo.

From the post:


We wanted to get a better idea of where President-elect Donald Trump gets his information. So we analyzed everything he has tweeted since he launched his campaign to take a look at the links he has shared and the news sources they came from.

Step-by-step guide to the software and analysis Trump’s tweets!

Excellent!

Follow: @lamthuyvo.

Which public figure’s tweets are you going to track/analyze?

November 29, 2016

Gab – Censorship Lite?

Filed under: Free Speech,Social Media,Twitter — Patrick Durusau @ 5:52 pm

I submitted my email today at Gab and got this message:

Done! You’re #1320420 in the waiting list.

Only three rules:

Illegal Pornography

We have a zero tolerance policy against illegal pornography. Such material will be instantly removed and the owning account will be dealt with appropriately per the advice of our legal counsel. We reserve the right to ban accounts that share such material. We may also report the user to local law enforcement per the advice our legal counsel.

Threats and Terrorism

We have a zero tolerance policy for violence and terrorism. Users are not allowed to make threats of, or promote, violence of any kind or promote terrorist organizations or agendas. Such users will be instantly removed and the owning account will be dealt with appropriately per the advice of our legal counsel. We may also report the user to local and/or federal law enforcement per the advice of our legal counsel.

What defines a ‘terrorist organization or agenda’? Any group that is labelled as a terrorist organization by the United Nations and/or United States of America classifies as a terrorist organization on Gab.

Private Information

Users are not allowed to post other’s confidential information, including but not limited to, credit card numbers, street numbers, SSNs, without their expressed authorization.

If Gab is listening, I can get the rules down to one:

Court Ordered Removal

When Gab receives a court order from a court of competent jurisdiction ordering the removal of identified, posted content, at (service address), the posted, identified content will be removed.

Simple, fair, gets Gab and its staff out of the censorship business and provides a transparent remedy.

At no cost to Gab!

What’s there not to like?

Gab should review my posts: Monetizing Hate Speech and False News and Preserving Ad Revenue With Filtering (Hate As Renewal Resource), while it is in closed beta.

Twitter and Facebook can keep spending uncompensated time and effort trying to be universal and fair censors. Gab has the opportunity to reach up and grab those $100 bills flying overhead for filtered news services.

What is the New York Times if not an opinionated and poorly run filter on all the possible information it could report?

Apply that same lesson to social media!

PS: Seriously, before going public, I would go to the one court-based rule on content. There’s no profit and no wins in censoring any content on your own. Someone will always want more or less. Courts get paid to make those decisions.

Check with your lawyers but if you don’t look at any content, you can’t be charged with constructive notice of it. Unless and until someone points it out, then you have to follow DCMA, court orders, etc.

November 21, 2016

Preserving Ad Revenue With Filtering (Hate As Renewal Resource)

Filed under: Advertising,Facebook,Marketing,Twitter — Patrick Durusau @ 4:02 pm

Facebook and Twitter haven’t implemented robust and shareable filters for their respective content streams for fear of disturbing their ad revenue streams.* The power to filter feared as the power to exclude ads.

Other possible explanations include: Drone employment, old/new friends hired to discuss censoring content; Hubris, wanting to decide what is “best” for others to see and read; NIH (not invented here), which explains silence concerning my proposals for shareable content filters; others?

* Lest I be accused of spreading “fake news,” my explanation for the lack of robust and shareable filters on content on Facebook and Twitter is based solely on my analysis of their behavior and not any inside leaks, etc.

I have a solution for fearing filters as interfering with ad revenue.

All Facebook posts and Twitter tweets, will be delivered with an additional Boolean field, ad, which defaults to true (empty field), meaning the content can be filtered. (following Clojure) When the field is false, that content cannot be filtered.

Filters being registered and shared via Facebook and Twitter, testing those filters for proper operation (and not applying them if they filter ad content) is purely an algorithmic process.

Users pay to post ad content, a step where the false flag can be entered, resulting in no more ad freeloaders being free from filters.

What’s my interest? I’m interested in the creation of commercial filters for aggregation, exclusion and creating a value-add product based on information streams. Moreover, ending futile and bigoted attempts at censorship seems like a worthwhile goal to me.

The revenue potential for filters is nearly unlimited.

The number of people who hate rivals the number who want to filter the content seen by others. An unrestrained Facebook/Twitter will attract more hate and “fake news,” which in turn will drive a great need for filters.

Not a virtuous cycle but certainly a profitable one. Think of hate and the desire to censor as renewable resources powering that cycle.

PS: I’m not an advocate for hate and censorship but they are both quite common. Marketing is based on consumers as you find them, not as you wish they were.

November 17, 2016

Mute Account vs. Mute Word/Hashtag – Ineffectual Muting @Twitter

Filed under: Free Speech,Tweets,Twitter — Patrick Durusau @ 10:55 am

twitter-hate-speech-460

I mentioned yesterday the distinction between muting an account versus the new muting by word or #hashtag at Twitter.

Take a moment to check my sources at Twitter support to make sure I have the rules correctly stated. I’ll wait.

(I’m not a journalist but readers should be enabled to satisfy themselves claims I make are at least plausible.)

No feedback from Twitter on the don’t appear in your timeline vs. do appear in your timeline distinction.

Why would I want to only block notifications of what I think of as hate speech and still have those tweets in my timeline?

Then it occurred to me:

If you can block tweets from appearing in your timeline by word or hashtag, you can block advertising tweets from appearing in your timeline.

You cannot effectively mute hate speech @Twitter because you could also mute advertising.

What about it Twitter?

Must feminists, people of color, minorities of all types be subjected to hate speech in order to preserve your revenue streams?


Not that I object to Twitter having revenue streams from advertising but it needs to be more sophisticated than the Nigerian spammer model now in use. Charge a higher price for targeted advertising that users are unlikely to block.

For example, I would be highly unlikely to block ads for cs theory/semantic integration tomes. On the other hand, I would follow a mute list that blocked histories of famous cricket matches. (Apologies to any cricket players in the audience.)

In my post: Twitter Almost Enables Personal Muting + Roving Citizen-Censors I offer a solution that requires only minor changes based on data Twitter already collects plus regexes for muting. It puts what you see entirely in the hands of users.

That enables Twitter to get out of the censorship business altogether, something it doesn’t do well anyway, and puts users in charge of what they see. A win-win from my perspective.

Alt-right suspensions lay bare Twitter’s consistency [hypocrisy] problem

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

Alt-right suspensions lay bare Twitter’s consistency problem by Nausicaa Renner.

From the post:

TWITTER SUSPENDED A NUMBER OF ACCOUNTS associated with the alt-right, USA Today reported this morning. This move was bound to be divisive: While Twitter has banned and suspended users in the past (prominently, Milo Yiannopoulos for incitement), USA Today points out the company has never suspended so many at once—at least seven in this case. Richard Spencer, one of the suspended users and prominent alt-righter, also had a verified account on Twitter. He claims, “I, and a number of other people who have just got banned, weren’t even trolling.”

If this is true, it would be a powerful political statement, indeed. As David Frum notes in The Atlantic, “These suspensions seem motivated entirely by viewpoint, not by behavior.” Frum goes on to argue that a kingpin strategy on Twitter’s part will only strengthen the alt-right’s audience. But we may never know Twitter’s reasoning for suspending the accounts. Twitter declined to comment on its moves, citing privacy and security reasons.

(emphasis in original)

Contrary to the claims of the Southern Poverty Law Center (SPLC) to Twitter, these users may not have been suspended for violating Twitter’s terms of service, but for their viewpoints.

Like the CIA, FBI and NSA, Twitter uses secrecy to avoid accountability and transparency for its suspension process.

The secrecy – avoidance of accountability/transparency pattern is one you should commit to memory. It is quite common.

Twitter needs to develop better muting options for users and abandon account suspension (save on court order) altogether.

November 16, 2016

Twitter Almost Enables Personal Muting + Roving Citizen-Censors

Filed under: Censorship,Free Speech,Tweets,Twitter — Patrick Durusau @ 12:40 pm

Investigating news reports of Twitter enabling muting of words and hashtags lead me to Advanced muting options on Twitter. Also relevant is Muting accounts on Twitter.

Alex Hern‘s post: Twitter users to get ability to mute words and conversations prompted this search because I found:

After nine years, Twitter users will finally be able to mute specific conversations on the site, as well as filter out all tweets with a particular word or phrase from their notifications.

The much requested features are being rolled out today, according to the company. Muting conversations serves two obvious purposes: users who have a tweet go viral will no longer have to deal with thousands of replies from strangers, while users stuck in an interminable conversation between people they don’t know will be able to silently drop out of the discussion.

A broader mute filter serves some clear general uses as well. Users will now be able to mute the names of popular TV shows, for instance, or the teams playing in a match they intend to watch later in the day, from showing up in their notifications, although the mute will not affect a user’s main timeline. “This is a feature we’ve heard many of you ask for, and we’re going to keep listening to make it better and more comprehensive over time,” says Twitter in a blogpost.

to be too vague to be useful.

Starting with Advanced muting options on Twitter, you don’t have to read far to find:

Note: Muting words and hashtags only applies to your notifications. You will still see these Tweets in your timeline and via search. The muted words and hashtags are applied to replies and mentions, including all interactions on those replies and mentions: likes, Retweets, additional replies, and Quote Tweets.

That’s the second paragraph and displayed with a high-lighted background.

So, “muting” of words and hashtags only stops notifications.

“Muted” offensive or inappropriate content is still visible “in your timeline and search.”

Perhaps really muting based on words and hashtags will be a paid subscription feature?

The other curious aspect is that “muting” an account carries an entirely different meaning.

The first sentence in Muting accounts on Twitter reads:

Mute is a feature that allows you to remove an account’s Tweets from your timeline without unfollowing or blocking that account.

Quick Summary:

  • Mute account – Tweets don’t appear in your timeline.
  • Mute by word or hashtag – Tweets do appear in your timeline.

How lame is that?

Solution That Avoids Censorship

The solution to Twitter’s “hate speech,” which means different things to different people isn’t hard to imagine:

  1. Mute by account, word, hashtag or regex – Tweets don’t appear in your timeline.
  2. Mute lists can be shared and/or followed by others.

Which means that if I trust N’s judgment on “hate speech,” I can follow their mute list. That saves me the effort of constructing my own mute list and perhaps even encourages the construction of public mute lists.

Twitter has the technical capability to produce such a solution in short order so you have to wonder why they haven’t? I have no delusion of being the first person to have imagined such a solution. Twitter? Comments?

The Alternative Solution – Roving Citizen-Censors

The alternative to a clean and non-censoring solution is covered in the USA Today report Twitter suspends alt-right accounts:

Twitter suspended a number of accounts associated with the alt-right movement, the same day the social media service said it would crack down on hate speech.

Among those suspended was Richard Spencer, who runs an alt-right think tank and had a verified account on Twitter.

The alt-right, a loosely organized group that espouses white nationalism, emerged as a counterpoint to mainstream conservatism and has flourished online. Spencer has said he wants blacks, Asians, Hispanics and Jews removed from the U.S.

[I personally find Richard Spencer’s views abhorrent and report them here only by way of example.]

From the report, Twitter didn’t go gunning for Richard Spencer’s account but the Southern Poverty Law Center (SPLC) did.

The SPLC didn’t follow more than 100 white supermacists to counter their outlandish claims or to offer a counter-narrative. They followed to gather evidence of alleged violations of Twitter’s terms of service and to request removal of those accounts.

Government censorship of free speech is bad enough, enabling roving bands of self-righteous citizen-censors to do the same is even worse.

The counter-claim that Twitter isn’t the government, it’s not censorship, etc., is intellectually and morally dishonest. Technically true in U.S. constitutional law sense but suppression of speech is the goal and that’s censorship, whatever fig leaf the SPLC wants to put on it. They should be honest enough to claim and defend the right to censor the speech of others.

I would not vote in their favor, that is to say they have a right to censor the speech of others. They are free to block speech they don’t care to hear, which is what my solution to “hate speech” on Twitter enables.

Support muting, not censorship or roving bands of citizen-censors.

November 6, 2016

Debate Night Twitter: Analyzing Twitter’s Reaction to the Presidential Debate

Filed under: Data Mining,Government,Twitter — Patrick Durusau @ 5:34 pm

Debate Night Twitter: Analyzing Twitter’s Reaction to the Presidential Debate by George McIntire.

A bit dated content-wise but George covers techniques, from data gathering to analysis, useful for future events. Possible Presidential inauguration riots on January 20, 2017 for example. Or, the 2017 Super Bowl, where Lady GaGa will be performing.

From the post:

This past Sunday, Donald Trump and Hillary Clinton participated in a town hall-style debate, the second of three such events in this presidential campaign. It was an extremely contentious affair that reverberated across social media.

The political showdown was massively anticipated; the negative atmosphere of the campaign and last week’s news of Trump making lewd comments about women on tape certainly contributed to the fire. Trump further escalated the immense tension by holding a press conference with women who’ve accused former President Bill Clinton of abusing.

With having a near unprecedented amount of attention and hostility, I wanted to gauge Twitter’s reaction to the event. In this project, I streamed tweets under the hashtag #debate and analyzed them to discover trends in Twitter’s mood and how users were reacting to not just the debate overall but to certain events in the debate.

What techniques will you apply to your tweet data sets?

November 2, 2016

How To Use Twitter to Learn Data Science (or anything)

Filed under: Data Science,Twitter — Patrick Durusau @ 7:55 pm

How To Use Twitter to Learn Data Science (or anything) by Data Science Renee.

Judging from the date on the post (May 2016), Renee’s enthusiasm for Twitter came before her recently breaking 10,000 followers on Twitter. (Congratulations!)

The one thing I don’t see Renee mentioning is the use of your own Twitter account to gain experience with a whole range of data mining tools.

Your Twitter feed will quickly out-strip your ability to “keep up,” so how do you propose to deal with that problem?

Renee suggests limiting examination of your timeline (in part), but have you considered using machine learning to assist you?

Or visualizing your areas of interests or people that you follow?

Indexing resources pointed to in tweets?

NLP processing of tweets?

Every tool of data science that you will be using for clients is relevant to your own Twitter feed.

What better way to learn tools than using them on content that interests you?

Enjoy!

BTW, follow Data Science Renee for a broad range of data science tools and topics!

October 23, 2016

Monetizing Twitter Trolls

Filed under: #gamergate,Tweets,Twitter — Patrick Durusau @ 2:21 pm

Alex Hern‘s coverage of Twitter’s fail-to-sell story, Did trolls cost Twitter $3.5bn and its sale?, is a typical short on facts story about abuse on Twitter.

When I say short on facts, I don’t deny any of the anecdotal accounts of abuse on Twitter and other social media.

Here’s the data problem with abuse at Twitter:

As of May of 2016, Twitter had 310 million active monthly users over 1.3 billion accounts.

Number of Twitter users who are abusive (trolls): unknown

Number of Twitter users who are victims: unknown

Number of abusive tweets, daily/weekly/monthly: unknown

Type/frequency of abusive tweets, language, images, disclosure: unknown

Costs to effectively control trolls: unknown

Trolls and abuse should be opposed both at Twitter and elsewhere, but without supporting data, creating corporate priorities and revenues to effectively block (not end, block) abuse isn’t possible.

Since troll hunting at present is a drain on the bottom line with no return for Twitter, what if Twitter were to monetize its trolls?

That is create a mechanism whereby trolls became the drivers of a revenue stream from Twitter.

One such approach would be to throw off all the filtering that Twitter does as part of its basic service. If you have Twitter basic service, you will see posts from everyone from committed jihadists to the Federal Reserve. Not blocked accounts, no deleted accounts, etc.

Twitter removes material under direct court order only. Put the burden and expense on going to court for every tweet on both individuals and governments. No exceptions.

Next, Twitter creates the Twitter+ account, where for an annual fee, users can access advanced filtering that includes blocking people, language, image analysis of images posted to them, etc.

Price point experiments should set the fees for Twitter+ accounts. Filtering will be a decision based on real revenue numbers. Not flights of fancy by the Guardian or Sales Force.

BTW, the open Twitter I suggest creates more eyes for ads, which should also improve the bottom line at Twitter.

An “open” Twitter will attract more trolls and drive more users to Twitter+ accounts.

Twitter trolls generate the revenue to fight them.

I rather like that.

You?

Twitter Logic: 1 call on Github v. 885,222 calls on Twitter

Filed under: Design,Tweets,Twitter — Patrick Durusau @ 1:24 pm

Chris Albon’s collection of 885,222 tweets (ids only) for the third presidential debate of 2016 proves bad design decisions aren’t only made inside the Capital Beltway.

Chris could not post his tweet collection, only the tweet ids under Twitter’s terms of service.

The terms of service reference the Developer Policy and under that policy you will find:


F. Be a Good Partner to Twitter

1. Follow the guidelines for using Tweets in broadcast if you display Tweets offline.

2. If you provide Content to third parties, including downloadable datasets of Content or an API that returns Content, you will only distribute or allow download of Tweet IDs and/or User IDs.

a. You may, however, provide export via non-automated means (e.g., download of spreadsheets or PDF files, or use of a “save as” button) of up to 50,000 public Tweets and/or User Objects per user of your Service, per day.

b. Any Content provided to third parties via non-automated file download remains subject to this Policy.
…(emphasis added)

Just to be clear, I find Twitter extremely useful for staying current on CS research topics and think developers should be “…good partners to Twitter.”

However, Chris is prohibited from posting a data set of 885,222 tweets on Gibhub, where users could download it with no impact on Twitter, versus every user who want to explore that data set must submit 885,222 requests to Twitter servers.

Having one hit on Github for 885,222 tweets versus 885,222 on Twitter servers sounds like being a “good partner” to me.

Multiple that by all the researchers who are building Twitter data sets and the drain on Twitter resources grows without any benefit to Twitter.

It’s true that someday Twitter might be able to monetize references to its data collections, but server and bandwidth expenses are present line items in their budget.

Enabling the distribution of full tweet datasets is one step towards improving their bottom line.

PS: Please share this with anyone you know at Twitter. Thanks!

Political Noise Data (Tweets From 3rd 2016 Presidential Debate)

Filed under: Government,Politics,Tweets,Twitter — Patrick Durusau @ 12:42 pm

Chris Albon has collected data on 885,222 debate tweets from the third Presidential Debate of 2016.

As you can see from the transcript, it wasn’t a “debate” in any meaningful sense of the term.

The quality of tweets about that debate are equally questionable.

However, the people behind those tweets vote, buy products, click on ads, etc., so despite my title description as “political noise data,” it is important political noise data.

To conform to Twitter terms of service, Chris provides the relevant tweet ids and a script to enable construction of your own data set.

BTW, Chris includes his Twitter mining scripts.

Enjoy!

August 29, 2016

ISIS Turns To Telegram App After Twitter Crackdown [Farce Alert + My Telegram Handle]

Filed under: Censorship,Cybersecurity,Encryption,Government,Telegram App,Twitter — Patrick Durusau @ 4:01 pm

ISIS Turns To Telegram App After Twitter Crackdown

From the post:

With the micro-blogging site Twitter coming down heavily on ISIS-sponsored accounts, the terrorist organisation and its followers are fast joining the heavily-encrypted messaging app Telegram built by a Russian developer.

On Telegram, the ISIS followers are laying out detailed plans to conduct bombing attacks in the west, voanews.com reported on Monday.

France and Germany have issued statements that they now want a crackdown against them on Telegram.

“Encrypted communications among terrorists constitute a challenge during investigations. Solutions must be found to enable effective investigation… while at the same time protecting the digital privacy of citizens by ensuring the availability of strong encryption,” the statement said.

Really?

Oh, did you notice the source? “Voanews.com reported on Monday.”

If you skip over to that post: IS Followers Flock to Telegram After being Driven from Twitter (I don’t want to shame the author so omitting their name), it reads in part:

With millions of IS loyalists communicating with one another on Telegram and spreading their message of radical Islam and extremism, France and Germany last week said that they want a continent wide effort to allow for a crackdown on Telegram.

“Encrypted communications among terrorists constitute a challenge during investigations,” France and Germany said in a statement. “Solutions must be found to enable effective investigation… while at the same time protecting the digital privacy of citizens by ensuring the availability of strong encryption.”

On private Telegram channels, IS followers have laid out detailed plans to poison Westerners and conduct bombing attacks, reports say.

What? “…millions of IS loyalists…?” IS in total is about 30K of active fighters, maybe. Millions of loyalists? Documentation? Citation of some sort? Being the Voice of America, I’d say they pulled that number out of a dark place.

Meanwhile, while complaining about the strong encryption, they are party to:

detailed plans to poison Westerners and conduct bombing attacks, reports say.

You do know wishing Westerners would choke on their Fritos doesn’t constitute a plan. Yes?

Neither does wishing to have an unspecified bomb, to be exploded at some unspecified location, at no particular time, constitute planning either.

Not to mention that “reports say” is a euphemism for: “…we just made it up.”

Get yourself to Telegram!

telegram-01-460

telegram-03-460

They left out my favorite:

Annoy governments seeking to invade a person’s privacy.

Reclaim your privacy today! Telegram!


Caveat: I tried using one device for the SMS to setup my smartphone. Nada, nyet, no joy. Had to use my cellphone number to setup the account on the cellphone. OK, but annoying.

BTW, on Telegram, my handle is @PatrickDurusau.

Yes, my real name. Which excludes this account from anything requiring OpSec. 😉

August 28, 2016

Twitter Said to Work on Anti-Harassment Keyword Filtering Tool [Good News!]

Filed under: Filters,Tweets,Twitter — Patrick Durusau @ 8:08 pm

Twitter Said to Work on Anti-Harassment Keyword Filtering Tool by Sarah Frier.

From the post:

Twitter Inc. is working on a keyword-based tool that will let people filter the posts they see, giving users a more effective way to block out harassing and offensive tweets, according to people familiar with the matter.

The San Francisco-based company has been discussing how to implement the tool for about a year as it seeks to stem abuse on the site, said the people, who asked not to be identified because the initiative isn’t public. By using keywords, users could block swear words or racial slurs, for example, to screen out offenders.

Nice to have good news to report about Twitter!

Suggestions before the code gets set in stone:

  • Enable users to “follow” filters of other users
  • Enable filters to filter on nicknames in content and as sender
  • Regexes anyone?

A big step towards empowering users!

August 14, 2016

Another Data Point On Twitter Censorship Practices

Filed under: #gamergate,Censorship,Free Speech,Twitter — Patrick Durusau @ 1:07 pm

twitter-censor-olympics-460

August 13, 2016

Twitter Censor Strikes Again (and again, and again)

Filed under: Censorship,Free Speech,Twitter — Patrick Durusau @ 3:54 pm

Twitter censors accounts for reasons known only to itself, but in the case, truth telling is one obvious trigger for Twitter censorship:

twitter-censors-again-460

Twitter censors accounts every day that don’t make the news and those are just as serious violations of free speech as this instance.

Twitter could trivially empower users to have free speech and the equally important right to not listen but also for reasons known only to Twitter, has chosen not to do so.

Free speech and the right to not listen are equally important.

What’s so difficult to understand about that?

August 11, 2016

“A Honeypot For Assholes” [How To Monetize Assholes/Abuse]

Filed under: Tweets,Twitter — Patrick Durusau @ 2:33 pm

“A Honeypot For Assholes”: Inside Twitter’s 10-Year Failure To Stop Harassment by Charlie Warzel.

From the post:

For nearly its entire existence, Twitter has not just tolerated abuse and hate speech, it’s virtually been optimized to accommodate it. With public backlash at an all-time high and growth stagnating, what is the platform that declared itself “the free speech wing of the free speech party” to do? BuzzFeed News talks to the people who’ve been trying to figure this out for a decade.

Warzel’s 6,000 word (5966 by my count) ramble uses “abuse” without ever defining the term. Nor do any of the people quoted in his post. But, like Justice Stewart, they “know it when they see it.”

One of the dangers Warzel’s post is every reader will insert their definition of “abuse.” Hard to find people who disagree that “abuse as they define it” should be blocked by Twitter.

All of Warzel’s examples are “abuse” (IMHO) but even so, I don’t support Twitter blocking that content from being posted. I emphasize posted because being posted on Twitter doesn’t obligate any user to read the content.

I don’t support Twitter censorship of any account, for any reason. Four Horsemen Of Internet Censorship + One.

If Twitter doesn’t block content, then how do to deal with “abuse?”

Why not monetize the blocking of assholes and abuse?

Imagine a Twitter client/app that:

  1. Maintains a list of people blocked not only by a user but allowed a user to subscribe to block lists of any other user.
  2. Employed stop lists, regexes, neural networks to filter tweets from people who have not been blocked.
  3. Neural networks trained on collections of “dick pics” and other offensive content to filter visual content as well.

Every user can have a customized definition of “abuse” for their own feed. Without impinging on the definitions of “abuse” of other users.

Twitter clients to support such filtering options are already in place. TweetDeck Versus Hootsuite – The Essential Guide discusses two popular clients. There are hundreds of others, both web and smart phone based.

Circling the question: “Why isn’t Twitter using my personal definition of “abuse” to protect me for free?” generates a lot of discussion, but no viable solutions.

Monetizing filtering of assholes and abuse, resources available in vast quantities, protects both free speech and freedom from unwanted speech.

The only useful question on Twitter abuse is the price point to set for avoiding X amount of abuse?

Yes?

August 10, 2016

Twitter Censorship On Behalf Of Turkish Government

Filed under: Censorship,Free Speech,Government,Tweets,Twitter — Patrick Durusau @ 11:05 am

twitter-turkey-censor-460

The link Post Coup Censorship takes you to a list of twenty-three (23) journalist/publicist accounts verified as withheld by Twitter in Turkey.

I have tweeted to Efe Kerem Sözeri about this issue and was advised the censorship is based on IP addresses. Sözeri points out that use of a VPN is one easy means of avoiding the censorship.

Hopefully that was productive than a rant about Twitter’s toadyism and self-anointed role to prevent abuse (as opposed to empowering Twitter users to avoid abuse on their own).

August 5, 2016

Your Next Favorite Twitter Account: @DeepDrumpf

Filed under: Neural Networks,Politics,Twitter — Patrick Durusau @ 2:25 pm

@DeepDrumpf is a Neural Network trained on Donald Trump transcripts.

If you are curious beyond the tweets, see: Postdoc’s Trump Twitterbot Uses AI To Train Itself On Transcripts From Trump Speeches.

Ideally an interface would strip @DeepDrumpf and @realDonaldTrump off of tweets and present you with the option to assign authorship to @DeepDrumpf or @realDonaldTrump.

At the end of twenty or thirty tweets, you get your accuracy score over assignment of authorship.

Enjoy!

July 21, 2016

Twitter Nanny Says No! No!

Filed under: Censorship,Free Speech,News,Reporting,Tweets,Twitter — Patrick Durusau @ 2:36 pm

twitter-nanny-460

For the other side of this story, enjoy Milo Yiannopoulos’s Twitter ban, explained by Aja Romano, where Aja is supportive of Twitter and its self-anointed role as arbiter of social values.

From my point of view, the facts are fairly simple:

Milo Yiannopoulos (formerly @Nero) has been banned from Twitter on the basis of his speech and the speech of others who agree with him.

What more needs to be said?

I have not followed, read, reposted or retweeted any tweets by Milo Yiannopoulos (formerly @Nero). And would not even if someone sent them to me.

I choose to not read that sort of material and so can anyone else. Including the people who complain in Aja’s post.

The Twitter Nanny becomes censor in insisting that no one be able to read tweets from Milo Yiannopoulos (formerly @Nero).

I’ve heard the argument that the First Amendment doesn’t apply to Twitter, which is true, but irrelevant. Only one country in the world has the First Amendment as stated in the US Constitution but that doesn’t stop critics from decrying censorship by other governments.

Or is it only censorship if you agree with the speech being suppressed?

Censorship of speech that I find disturbing, sexist, racist, misogynistic, dehumanizing, transphobic, homophobic, supporting terrorism, is still censorship.

And it is still wrong.

We only have ourselves to blame for empowering Twitter to act as a social media censor. Central point of failure and all that jazz.

Suggestions on a free speech alternative to Twitter?

May 16, 2016

Twitter Giveth and Taketh Away (NSA as Profit Center?)

Filed under: Intelligence,NSA,Twitter — Patrick Durusau @ 9:39 am

Twitter Giveth: GCHQ intelligence agency joins Twitter. Just about anyone can get a Twitter account these days.

Do see the GCHQ GitHub site for shared software.

Taketh Away Twitter Bars Intelligence Agencies From Using Analytics Service.

Twitter has barred Dataminr from providing services to government intelligence services.

Dataminr monitors the entire Twitter pipe and provides analytics based on that stream.

Will this result in the NSA sharing its signal detection in the Twitter stream with other intelligence agencies?

Or for that matter, the NSA could start offering commercial signal detection services across all its feeds. Make it a profit center for the government rather than a money pit.

BTW, don’t be deceived by the illusion of space between government and Twitter, or any other entity that cooperates with a national government. Take “compromised” as a given. The real questions are by who and for what purpose?

April 25, 2016

Peda(bot)bically Speaking:…

Filed under: Journalism,Machine Learning,News,Reporting,Twitter — Patrick Durusau @ 8:32 pm

Peda(bot)bically Speaking: Teaching Computational and Data Journalism with Bots by Nicholas Diakopoulos.

From the post:

Bots can be useful little creatures for journalism. Not only because they help us automate tasks like alerting and filtering, but also because they encapsulate how data and computing can work together, in service of automated news. At the University of Maryland, where I’m a professor of journalism, my students are using the power of news bots to learn concepts and skills in computational journalism—including both editorial thinking and computational thinking.

Hmmm, bot that filters all tweets that don’t contain a URL? (To filter cat pics and the like.) 😉

Or retweets tweets with #’s that trigger creation of topics/associations?

I don’t think there is a requirement that hashtags be meaningful to others. Yes?

Sounds like a great class!

Women in Data Science (~632) – Twitter List

Filed under: Data Science,Twitter — Patrick Durusau @ 10:07 am

Data Science Renee has a twitter list of approximately 632 women in data science.

I say “approximately” because when I first saw her post about the list it had 630 members. When I looked this AM, it had 632 members. By the time you look, that number will be different again.

If you are making a conscious effort to seek a diversity of speakers for your next data science conference, it should be on your list of sources.

Enjoy!

April 8, 2016

1880 Big Data Influencers in CSV File

Filed under: BigData,Twitter,Web Scrapers — Patrick Durusau @ 10:16 am

If you aren’t familiar with Right Relevance, you are missing an amazing resource for cutting through content clutter.

Starting at the default homepage:

rightrelevance-01

You can search for “big data” and the default result screen appears:

influencers-02

If you switch to “people,” the following screen appears:

influencers-03

The “topic score” line moves, so you can require a higher or lesser score for inclusion in the listing. That is helpful if you want only the top people, articles, etc. on a topic or want to reach deeper into the pool of data.

As of yesterday, if you set the “topic score” to the range 70 to 98, the number of people influencers was 1880.

The interface allows you to follow and/or tweet to any of those 1880 people, but only one at a time.

I submitted feedback to Right Relevance on Monday of this week pointing out how useful lists of Twitter handles could be for creating Twitter seed lists, etc., but have not gotten a response.

Part of my query to Right Relevance concerned the failure of a web scraper to match the totals listed in the interface (a far lower number of results than expected).

In the absence of an answer, I continue to experiment with the Web Scraper extension for Chrome to extract data from the site.

Caveat: In order to set the delay for requests in Web Scraper, I have found the settings under “Scrape” ineffectual:

web-scraper-01

In order to induce enough delay to capture the entire list, I set the delay in the exported sitemap (in JSON) and then imported it into another sitemap. Could have reached the same point by setting the delay under the top selector, which was also set to SelectorElementScroll.

To successfully retrieve the entire list, that delay setting was 16000 miliseconds.

There may be more performant solutions but since it ran in a separate browser tab and notified me of completion, time wasn’t an issue.

I created a sitemap that obtains the user’s name, Twitter handle and number of Twitter followers, bigdata-right-relevance.txt.

Oh, the promised 1880-big-data-influencers.csv. (File renamed post-scraping due to naming constraints in Web Scraper.)

At best I am a casual user of Web Scraper so suggestions for improvements, etc., are greatly appreciated.

March 31, 2016

Onlinecensorship.org Launches First Report (PDF)

Filed under: Censorship,Free Speech,Social Media,Tweets,Twitter — Patrick Durusau @ 2:36 pm

Onlinecensorship.org Launches First Report (PDF).

Reposting:

Onlinecensorship.org is pleased to share our first report "Unfriending Censorship: Insights from four months of crowdsourced data on social media censorship." The report draws on data gathered directly from users between November 2015 and March 2016.

We asked users to send us reports when they had their content or accounts taken down on six social media platforms: Facebook, Flickr, Google+, Instagram, Twitter, and YouTube. We have aggregated and analyzed the collected data across geography, platform, content type, and issue areas to highlight trends in social media censorship. All the information presented here is anonymized, with the exception of case study examples we obtained with prior approval by the user.

Here are some of the highlights:

  • This report covers 161 submissions from 26 countries, regarding content in eleven languages.
  • Facebook was the most frequently reported platform, and account suspensions were the most reported content type.
  • Nudity and false identity were the most frequent reasons given to users for the removal of their content.
  • Appeals seem to present a particular challenge. A majority of users (53%) did not appeal the takedown of their content, 50% of whom said they didn’t know how and 41.9% of whom said they didn’t expect a response. In only four cases was content restored, while in 50 the user didn’t get a response.
  • We received widespread reports that flagging is being used for censorship: 61.6% believed this was the cause of the content takedown.

While we introduced some measures to help us verify reports (such as giving respondents the opportunity to send us screenshots that support their claims), we did not work with the companies to obtain this data and thus cannot claim it is representative of all content takedowns or user experiences. Instead, it shows how a subset of the millions of social media users feel about how their content takedowns were handled, and the impact it has had on their lives.

The full report is available for download and distribution under Creative Commons licensing.

As the report itself notes, 161 reports across 6 social media platforms in 4 months isn’t a representative sample of censoring in social media.

Twitter alone brags about closing 125,000 ISIS accounts since mid-2015 (report dated 5 February 2016).

Closing ISIS accounts is clearly censorship of political speech, whatever hand waving and verbal gymnastics Twitter wants to employ to justify its practices. Including terms of service.

Censorship, on whatever basis, by whoever practiced, by whatever mechanism (including appeals), will always step on legitimate speech of some speakers.

The non-viewing of content has one and only one legitimate locus of control, a user’s browser for web content.

Browsers and/or web interfaces for Twitter, Facebook, etc., should enable users to block users, content by keywords, or even classifications offered by social media services.

Poof!

All need for collaboration with governments, issues of what content to censor, appeal processes, etc., suddenly disappear.

Enabling users to choose the content that will be displayed in their browsers empowers listeners as well as speakers, with prejudice towards none.

Yes?

March 30, 2016

Tay AI Escapes, Recaptured

Filed under: Artificial Intelligence,Twitter — Patrick Durusau @ 3:35 pm

Microsoft’s offensive chatbot Tay returns, by mistake by Georgia Wells.

From the post:

Less than one week after Microsoft Corp. made its debut and then silenced an artificially intelligent software chatbot that started spewing anti-Semitic rants, a researcher inadvertently put the chatbot, named Tay, back online. The revived Tay’s messages were no less inappropriate than before.

I remembered a DARPA webinar (download and snooze) but despite following Tay I missed her return.

Looks like I need a better tracking/alarm system for incoming social media.

I see more than enough sexist, racist, bigotry in non-Twitter news feeds to not need any more but I prefer to make my own judgments about “inappropriate.”

Whether it is the FBI, FCC or private groups calling “inappropriate.”

March 24, 2016

AI Masters Go, Twitter, Not So Much (Log from @TayandYou?)

Filed under: Artificial Intelligence,Games,Machine Learning,Twitter — Patrick Durusau @ 8:30 pm

Microsoft deletes ‘teen girl’ AI after it became a Hitler-loving sex robot within 24 hours by Helena Horton.

From the post:

A day after Microsoft introduced an innocent Artificial Intelligence chat robot to Twitter it has had to delete it after it transformed into an evil Hitler-loving, incestual sex-promoting, ‘Bush did 9/11’-proclaiming robot.

Developers at Microsoft created ‘Tay’, an AI modelled to speak ‘like a teen girl’, in order to improve the customer service on their voice recognition software. They marketed her as ‘The AI with zero chill’ – and that she certainly is.

The headline was suggested to me by a tweet from Peter Seibel:

Interesting how wide the gap is between two recent AI: AlphaGo and TayTweets. The Turing Test is *hard*. http://gigamonkeys.com/turing/.

In preparation for the next AI celebration, does anyone have a complete log of the tweets from Tay Tweets?

I prefer non-revisionist history where data doesn’t disappear. You can imagine the use Stalin would have made of that capability.

March 2, 2016

Muting users on Twitter – Achtung! State, DoD, Other US Censors

Filed under: Censorship,Government,Twitter — Patrick Durusau @ 5:12 pm

The Twitter Help Center has a great webpage titled: Muting users on Twitter.

From that page:

Mute is a feature that allows you to remove an account’s Tweets from your timeline without unfollowing or blocking that account. Muted accounts will not know that you’ve muted them and you can unmute them at any time. To access a list of accounts you have muted, visit your muted accounts settings on twitter.com or your app settings on Twitter for iOS or Android.

Instead of leaning on Twitter to close accounts, the State Department, Department of Defense and others can compile Twitter Mute Lists that have the Twitter accounts that any reasonable person should mute.

The Catholic News Service used to publish movie ratings in Our Sunday Visitor and while the rating system has changed since I last saw it (think 1960’s), it was a great way to pick out movies.

I think most ones I saw were either condemned or some similar category. 😉

A twitter mute list from State, DoD and others would save me time of searching for offensive content to view. I am sure that is true for others as well.

Oh, not to mention that people who are offended can choose to not view such content. Sorry, almost go carried away there.

How’s that for a solution to “propaganda” on Twitter? If it offends you, don’t look. Leave the rest of us the hell alone.

February 28, 2016

NCSU Offers Social Media Archives Toolkit for Libraries [Defeating Censors]

Filed under: Instagram,Library,Library software,Social Media,Twitter — Patrick Durusau @ 8:19 pm

NCSU Offers Social Media Archives Toolkit for Libraries by Matt Enis.

From the post:

North Carolina State University (NCSU) Libraries recently debuted a free, web-based social media archives toolkit designed to help cultural heritage organizations develop social media collection strategies, gain knowledge of ways in which peer institutions are collecting similar content, understand current and potential uses of social media content by researchers, assess the legal and ethical implications of archiving this content, and develop techniques for enriching collections of social media content at minimal cost. Tools for building and enriching collections include NCSU’s Social Media Combine—which pre-assembles the open source Social Feed Manager, developed at George Washington University for Twitter data harvesting, and NCSU’s own open source Lentil program for Instagram—into a single package that can be deployed on Windows, OSX, and Linux computers.

“By harvesting social media data (such as Tweets and Instagram photos), based on tags, accounts, or locations, researchers and cultural heritage professionals are able to develop accurate historical assessments and democratize access to archival contributors, who would otherwise never be represented in the historical record,” NCSU explained in an announcement.

“A lot of activity that used to take place as paper correspondence is now taking place on social media—the establishment of academic and artistic communities, political organizing, activism, awareness raising, personal and professional interactions,” Jason Casden, interim associate head of digital library initiatives, told LJ. Historians and researchers will want to have access to this correspondence, but unlike traditional letters, this content is extremely ephemeral and can’t be collected retroactively like traditional paper-based collections.

“So we collect proactively—as these events are happening or shortly after,” Casden explained.

I saw this too late today to install but I’m sure I will be posting about it later this week!

Do you see the potential of such tooling for defeating would-be censors of Twitter and other social media?

More on that later this week as well.

February 27, 2016

The Answer To Censors – Hand the Speaker a Larger Megaphone

Filed under: Censorship,Twitter — Patrick Durusau @ 8:03 pm

TheCthulhu tweeted yesterday:

cthulhusec-02

In case you are interested, the documents served on Twitter (in Turkish and English).

There is only one answer to censors – hand the censored speaker a larger megaphone.

Follow:

@YourAnonNews

@CryptOnymous

and for good measure:

@AnonyOps

OK, only slightly larger but every follower counts.

Are you going to increase the size of TheCthulhu‘s megaphone?

« Newer PostsOlder Posts »

Powered by WordPress