“Troll Watch: Trending Hashtags - NPR” plus 1 more
Posted: 11 Aug 2019 02:03 PM PDT
NPR's Michel Martin speaks with journalist Emily Stewart.
MICHEL MARTIN, HOST:
It's a big weekend in politics with a lot of Democratic contenders at the Iowa State Fair and different candidates making the benchmarks for the next scheduled debates in September. So that's one reason we thought it would be worthwhile to look back at the last round of debates. You might have noticed that hashtags like #DemDebateSoWhite and #KamalaHarrisDestroyed started trending, and you might have wondered why. Well, in the time since, we've learned more about what made those hashtags go viral and who was behind them, so we've decided to take this to our regular segment Troll Watch.
(SOUNDBITE OF MUSIC)
MARTIN: We're joined now by Emily Stewart. She's a reporter at Vox, and she recently wrote about the hashtag #KamalaHarrisDestroyed. She says it reveals how much we still don't understand about social media manipulation, and she's with us now.
Emily Stewart, welcome. Thanks for joining us.
EMILY STEWART: Thank you for having me.
MARTIN: So let's start with the conclusion and work backward. The trending hashtag #KamalaHarrisDestroyed - look, it's a reference to the confrontation between Hawaii Congresswoman Tulsi Gabbard when she criticized California Senator Kamala Harris' record as a prosecutor. So it was a moment, but there were people who thought it odd that it got so much traction and wondered whether bots or conservative activists were kind of pushing it out. So do we know?
STEWART: Well, I think that's sort of the big question here. And I think the answer is that it seems as though it is a combination. It looks like that specific hashtag was started by conservative activists, but then Fox found it and spread it and helped it to get farther than it might have otherwise. So that seems to be what happened.
But, you know, I think it reveals broader questions that we just really still do not know how social media manipulation works. And we can't figure out what to trust and what not to trust.
MARTIN: You say that Twitter and other platforms have improved their practices post-2016. They're still not perfect in your reporting. Do the social media companies take this seriously?
STEWART: They take it seriously to the extent that it would be a bad look if they didn't look like they were trying at all. But obviously, social media companies make money when we are there and we are engaged. And we know that what keeps people engaged is controversy. You know, you hear a lot of talk about social media bias.
Well, social media's bias is toward extremism, towards keeping people excited. And so, yes, does Facebook and Twitter and Google want to do a little bit better? Maybe. But it's not convenient for them to be boring. And so this sort of stuff is what drums people up and keeps people coming back.
MARTIN: One of the points that you make in the piece is this - I just want to read something from your piece. You said, it's not just the misinformation itself that sows division. It's also the debate about it. People are confused about what social media manipulation is, how it works and whether it's happening. And they've also got their own political motivations to believe whether or not it exists. You say that Harris's camp had an incentive to claim that negative hashtag about her is Russian propaganda, but her opponents have an incentive to brush it off. And so the more people debate what is and isn't fake news, the harder it becomes for voters to determine the truth.
Maybe this is sort of a tautology here, but I wonder if - could it possibly work the other way? That people perhaps can be better educated about whether they should hold back before they decide whether something's true because there's so much fog around it?
STEWART: Yeah. I mean, I think that there is - it's hard to say hold on and wait for all the information, especially now when the Internet has made communication so frictionless. I think it's important to keep motivations in mind, and it's good to hang back and wait for more information before you make conclusions. But it's also - I mean, it's human nature. It's hard to do sometimes.
MARTIN: That's Emily Stewart, reporter at Vox. We're talking about her piece "#KamalaHarrisDestroyed Debate Signals How Much We Still Don't Understand About Social Media Manipulation."
Emily, thanks so much for talking to us.
STEWART: Thank you.
MARTIN: This is NPR News.
NPR transcripts are created on a rush deadline by Verb8tm, Inc., an NPR contractor, and produced using a proprietary transcription process developed with NPR. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of NPR's programming is the audio record.
Posted: 14 Aug 2019 12:36 AM PDT
Global Computer Vision Software Market Research Report 2019 Overview :
Global Computer Vision Software Market Growth (Status and Outlook) 2019-2024 has its complete summary provided in such a pattern that the reader will get the consequences of the vital information associated with the Computer Vision Software market. The research study provides comprehensive data of manufacturers, regions, applications, and others. The report includes the competitive landscape by elaborating on the current mergers and acquisitions (M&A), venture funding, and product developments that took place in the market in the recent past. It provides product distribution, product demand, growth benefits, business flexibility, financial growth, and applications.
DOWNLOAD FREE SAMPLE REPORT: https://www.mrinsights.biz/report-detail/177136/request-sample
Analysis of Global Computer Vision Software Market 2019:-
At present, the market focuses on enhancing its global Computer Vision Software market status with the reference of the dominating players. The report highlights the demand for individual segment in each region. This statistical surveying report does estimations on the economic tactics, product supply and demand, applications, future forecast, and growth and development factors as well as a sales channel, direct marketing, indirect marketing, marketing channel future trend. Various graphical presentation techniques such as charts, graphs, tables, and pictures are used while developing this report. Different static, as well as dynamic aspects of the business, are studied in this analytical report.
The market statistics are portrayed in a very cear-cut format for the convenience of the readers. It comprises of top to bottom illumination of the past information along with the present and future needs. Additionally, an examination of current market designs and other basic characteristics all around the world is covered. The report covers estimation from a global aspect that contains a regional expansion class, along with Computer Vision Software market size, scope and benefit, and expenditure data. Moreover, the report has included ongoing industry trends and advances as well as preceding, existing, and estimated market size in terms of volume and value.
For competitor segment, the report includes global key players of the market as well as some small players: Microsoft, AWS, OpenCV, Google, Sight Machine, Scikit-image, Clarifai, Ximilar, Hive, IBM, Alibaba, Sighthound
On a regional basis, the global Computer Vision Software market can be segmented into:
Reasons To Purchase This Report:
There are 12 Chapters to deeply display the global Computer Vision Software market.
Chapter 1: Scope of the Report
Chapter 2: Executive Summary
Chapter 3: Global Computer Vision Software by Manufacturers
Chapter 4: Computer Vision Software by Regions
Chapter 5, 6, 7, 8 and 9: Americas,APAC,Europe,Middle East & Africa,Market Drivers, Challenges and Trends
Chapter 10 and 11: Global Computer Vision Software Market Forecast, Key Players Analysis
Chapter 12 : Research Findings and Conclusion.
Customization of the Report:This report can be customized to meet the client's requirements. Please connect with our sales team (email@example.com), who will ensure that you get a report that suits your needs.
Tom is a staff writer at Top News Herald. He covers technology news and handles all the technical stuff for Top News Herald. Tom originally hails from the UK and went to Foyle College.
|You are subscribed to email updates from "what s trending google" - Google News. |
To stop receiving these emails, you may unsubscribe now.
|Email delivery powered by Google|
|Google, 1600 Amphitheatre Parkway, Mountain View, CA 94043, United States|