Imagine meeting someone for the first time who comes from a distant country but is fluent in your language. There may appear to be no immediate communication barrier, so would you adapt the tone and cadence of your voice, or the spacing of pauses in your speech? How about altering your body language, mannerisms and facial expressions, depending on the background of the person in front of you? Would you sit or stand differently and pay attention to your hand gestures?
One day at graduate school, one of Lisa Feldman Barrett’s colleagues asked her out on a date. She didn’t really fancy him, but she had been in the lab all day and felt like a change of scenery, so she agreed to go to the local coffee shop. As they chatted, however, she started to become flushed in the face, her stomach was churning, and her head seemed to whirl. Maybe she was wrong, she thought: perhaps she really did like him. By the time they left, she’d already agreed to go on a second date.
On a vu ces dernières années une généralisation des nominations Chief Data Officers (CDOs) dans notre industrie financière. Au point que les prévisions du Gartner Group sont en passe de devenir une réalité dans l'ensemble des métiers de la banque, de la finance et de l'assurance, en France. Selon cet institut de prospective, 90 % des plus grandes entreprises mondiales seront dotées de Chief Data Officers (CDOs) à l'horizon 2019. Et Gartner dénombrait 400 CDOs en 2014, 1000 en 2015 et 2000 fin 2016.
"In the 1920s, an engineer’s 'half life of knowledge'—the time it took for half of his expertise to become obsolete—was thirty-five years. In the 1960s, it was a decade. Now it’s five years at most, and, for a software engineer, less than three" https://t.co/7NnpaeXnym
Muck Rack makes it simple to find people, tweets, or articles that mention any name, keyword, company, hashtag etc. We've compiled this guide to help you make the most of your search.
Selecting a term
Start searching tweets, articles from media outlets, articles mentioned in tweets, journalists'
names, titles and bios with some suggested searches:
Companies or Topics (e.g. iPhone, Microsoft)
Phrases (e.g. "cloud computing") — use quotes to keep the terms together
Twitter handles (e.g. @username) — returns those who have mentioned or replied to
Names (e.g. "David Pogue")
Hashtags (e.g. #sxsw, #london2012)
Bio details (e.g. vegan, Olympics, father)
Muck Rack's Advanced Search allows for many boolean operators.
Find results that mention multiple specified terms, use AND or
+. For example, ensure each result contains both Elon Musk and Mark Zuckerberg by
searching Musk AND Zuckerberg or Musk + Zuckerberg.
Use the operators OR or , to broaden your search when you'd like either of
multiple terms to appear in results. (This is the default behavior of our search when no operators
are used). For example, results will contain either cake or cookie by searching cake OR cookie or cake,cookie
Use NOT or - to subtract results from your search. For
example, searching Disney will yield results about the Walt Disney Company as well as Walt Disney
World Resort. To exclude mentions of Disney World, search for Disney -World or Disney
When using one of these operators with a phrase, enclose it in quotation marks. For example, you can
find results about smartphones excluding Apple's iPhone 4S by searching smartphone -"iPhone
Exact case matching or punctuation
If you're searching for a brand name or keyword that relies on specific punctuation marks or capitalization, you can
find results that match your exact query by adding matchcase: before the keyword you're searching for, like matchcase:E*TRADE .
Use parentheses to separate multiple
boolean phrases. For example, to find journalists talking about having fun in Disney World or
Disneyland, search for ("disney world" OR disneyland) AND fun.
An asterisk can be used to search for any variation of a root word truncated by the asterisk. For example, searching for admin* will return results for administrator, administration, administer, administered, etc.
A near operator is an AND operator where you can control the distance between the words. You can vary the distance the near operation uses by adding a forward slash and number (between 0-99) such as strawberries NEAR/10 "whipped cream", which means the strawberries must exist within 10 words of "whipped cream".