The Northern Lights of Twitter

It is March 17, 2015, and a solar storm is brewing. The strongest storm since August 2005. This means one thing: for much of the Northern Hemisphere, a good chance of seeing the Northern Lights, or Aurora Borealis.

If you want updates on where in the world you can see the Northern Lights, you can check NOAA’s real-time aurora forecast, but the map is not very intuitive and is hard to translate into “should I go outside and look right now?” So instead, I checked Twitter.

Click here for The Northern Lights of Twitter Map with Timestamps.

Click here for The Northern Lights of Twitter Storify.

According to Twitter users, the Northern Lights are visible tonight in Ontario, Alberta, Nebraska, Wisconsin, Minnesota, Maine, and Norway. (I performed the survey by monitoring the search term “northern lights” on Twitter, since it was more popular than the hashtag #NorthernLights, and cherry-picking geographically disparate locations to record. By the nature of the search I’m sure I missed many locations. Just while composing this post I have seen additional posts in Alaska, Sweden, Michigan, and Ireland.)

 

Twitter curation, not so easy…

After the last class I was still unclear what to think about Twitter and social medias as a way to report news. I was not a big Twitter user and this class made me use it more. I was curious to investigate more and see how good Twitter was to report on some heated subjects where having someone on the ground could be either difficult or could bring significant value and truth. After searching a few hashtags, I found it was virtually impossible to take anything for true unless methodically searching for clues on the veracity of the tweet. Also, many tweets were a vessel for articles and pictures and opening each content was sometime a mess. I thought through a few actions that could be useful to curate tweets and get a larger picture and tried to build that into a simple tool.

This is still more of an example on what could be done than something ready for daily usage but I tried to get a sense of what a curated twitter feed could look like. Being able to search for a subject, get translation (non-latin characters are still an issue in my tool), get attached pictures and article right at the same place, get past tweets of the same user, know his location if available and do a reverse query on attached image to know if it was already present on the web.

The work in progress can be found HERE, let me know what you think and I will continue to improve it as the time constraint didn’t allow me for more advanced features and a bug-proof solution yet.

How and why The Economist`s “Latino” Chili Peppers cover got Hispanic Americans “fired up”

I reported on the debate over Twitter about The Economist`s latest cover story and the concept used by the publication to talk about Latinos.

LATINO-PEPPERS-COVER-

 

The debate ranges between healthy criticism to some opportunism as news organizations that picked up the issue, just focus on the red peppers and not about the story. It is also interesting to see – and this is a opinion based on perception not fact – how the same cover seems to be interpreted differently in the US (very PC) and outside the country (not so PC). Unfortunately I did not have access to geolocated data to review in detail.

I used Fold for this (got a beta access yesterday). The story It`s still not publicly available. But I can show it in class.

Experimenting with Fold

 

Joys of the rumor mill: Putin disappears. Netizens have a ball.

I wrote this week’s social media-oriented piece about the mysterious 10-day disappearance of Russian President Vladimir Putin. Given the speed and scale of the virtual outpouring of speculations about his whereabouts, the story seemed particularly fitting for social media curation. I used Martin Hawksey’s TAGS [Twitter Archive Google Spreadsheets] to scrape some Twitter API for statistics, read through various hashtag archives related to the topic during this past week, and to generate the network visualizations.

See the entry on Medium here.

Stephen’s Curated Story: Mission Bay Fire (#sffire)

Yesterday evening, a fire broke out in an apartment building under construction in San Francisco’s Mission Bay neighborhood, near AT&T park. The fire eventually escalated to a 6-alarm rating, and nearly half of the city’s firefighters were eventually called in to battle the blaze. Using twXplorer, Keepr, and Storify‘s built-in social media navigator, I found and curated a series of tweets, Vines, and YouTube videos to tell the story:
http://storify.com/s2tephen/mission-bay-fire-sffire

What the World Ate for Breakfast

Screen Shot 2014-03-12 at 1.22.29 AM
http://www.pinterest.com/alex1sh0pe/what-the-world-ate-for-breakfast/

I wanted to do a story on what the world eats for breakfast, pieced together by posts from popular social networking tools in various countries. However, many social networks required in-country mobile phone numbers to join (e.g. Mixi in Japan), or had strict privacy settings to interact with other users (e.g. Line) and so I could not pull content from them.

My process involved finding a colloquial term for breakfast in the language of a variety of locations, and then trying to find a geo-tagged post with a picture of breakfast that I thought might be interesting, surprising, or just tasty looking. I was able to retrieve photos from Weibo, Instagram, Twitter, and Google Plus. I tried to find breakfast photos that looked more-or-less home-cooked, as opposed to photos from restaurants.

Once I found the photos, I put them on a Pinterest map. Take a tour of breakfast!

Fun facts:

Breakfast in German = Frühstück
Portuguese = “pequeno-almoço”
Russian = “завтрак”
Japanese = “朝食”
Turkish = “kahvaltı”

Toronto gets a cat video festival

I was poking around news sites to find events I might want to cover for this assignment. Lo and behold, I found out that Toronto was going to host its first “cat video festival.” What’s more, none other than the Prime Minister’s wife, Laureen Harper, will appear at the event.

I made this short commentary in Zeega about the news and reaction to the news.

I also collected reactions on Twitter using Storify.

Here are some highlights:

twitter rx1 twitter rxn3 twitter rxn2

Notes about process: Both Zeega and Storify were extremely intuitive and easy to use. I do, however, regret the fact that I could not embed cat videos in Zeega.