A unique blog dedicated to covering the worlds of book publishing and the news media, revealing creative ideas, practical strategies, interesting stories, and provocative opinions. Free speech, literacy, and great books are also discussed. Along the way, discover savvy but entertaining insights on book marketing, public relations, branding, and advertising from a veteran of two decades in the industry of book publishing publicity and marketing.
Saturday, April 6, 2019
Does Everybody Lie – To Authors?
authors-turned-marketers, writers need to know how to appeal to the hearts
and minds of consumers, and the media.Often, writers must tug at emotionally sensitive points in order for
their voices to be heard or their messages to resonate.But for writers to know what will stir people
to buy they will need to know what really moves people to act.Which facts, assumptions, and biases do others operate under that authors would benefit to know about?
recent New York Times best seller, Everybody Lies:Big Data, New Data and What the Internet CanTell Us About Who We Really Are, Seth Stephens-Davidowitz attempts to show us who we are by examining Google
searches, Facebook posts, and Twitter messages.It’s an interesting attempt, much like Freakonomics and TheDay America Told the Truth, tried to
reveal bigger truths beyond what our instincts, polls, or statistics state.
truth is we don’t know what the truth is.We know people lie to pollsters.That they have faulty memories.That they perceive differently from what they see, that they act
contrary to stated beliefs, and that they do not do what they say.So how is one to properly understand the
world he or she lives in, especially if we need to play on these behaviors and
views in order to sell a book to them?
author of Everybody Lies is a former
Google data scientist with a PhD. from Harvard, a lecturer at The Wharton
School, and a contributing op-ed writer for The
New York Times whose research has appeared in the Journal of Public
Economics.We’ll assume he’s qualified
to write this book, but I may be using the wrong data to make this
assumption.If I learned anything from
this book it is to question everything.
book brilliantly shows how data can contradict how things really appear to
be.But it also shows how data can be
misinterpreted.It fails to discuss
faulty problems in how data is gathered and it doesn’t take into account the
people who don’t search for things online or post on Facebook. It doesn't explore how their views,
patterns, or actions are not considered when putting the data together.His book raises as many questions as it
are some interesting conclusions the author draws from the data:
it comes to what men search for when it comes to their body, the number one
topic is penis size.The top concern for
women about their body is vaginal odor.
an examination of Facebook posts, we learn the choice of words varies greatly
amongst the sexes.For men, the most
common words used are fuck, fucking, bullshit, and shit.For women, it is shopping, love, soooo, and
cute.Men seem to focus their posts on
Xbox, government, fighting, football and economy while women write about baby,
mom, family, boyfriend and things regarding relationships.
an odd obsession:according to the book,
“Men make as many searches looking for ways to perform oral sex on themselves
as they do for how to give a woman an orgasm.”
tells us that search rates for “how to roll a joint” peak between 1 and 2 a.m.
and that search rates for “weather,” “prayer,” and “news” peak before 5:30 a.m.
it comes to stereotypes we learn that the search terms most associated with blacks is rude and racist, for Jews it’s evil and racist, for Muslims it’s evil
and terrorists, for Mexicans it’s racist and stupid, for Asians it’s ugly and
racist, for gays it’s evil and wrong, and for Christians it’s stupid and crazy.
we also learn that “Americans are Googling the word “nigger” with the same
frequency as “migraine” and “economist.”Further, “searches for “nigger jokes” are 17 x more common than searches
for “kike jokes,” “spic jokes,” “chink jokes” and “fag jokes” combined.
these stunning findings could be faulty.For instance, when they total up searches, they don’t examine the number
of people searching for something – just the frequency over a period of
time.Further, the terms people search
under are not completely reflective of what’s being searched for.Look at the term “kike jokes.”What about “Jew jokes”?For “spic” jokes, what about “Hispanic
jokes,” “Mexican jokes,” “wetback jokes” and other related terms?Lastly, who is doing the searching would be
of interest – does it break down based on certain demographics?
of the things covered in the book is the correlation of searches and
actions.Case in point.Every month, 3.5 million Google searches in
the U.S. relate to suicide, such as “suicidal,” “commit suicide” and “how to
suicide.”But, only about 3,000 suicides
occur each month. Now, not every search done is by someone considering suicide,
and not every person who killed himself even searched the term online, but it
shows that what appears to be an obsession by many is acted on by so few.
if you look at the fact that in 2014 there were about 6,000 searches for the
exact phrase “how to kill your girlfriend,” in that year 400 women were murdered by their boyfriends.But one can’t know for sure how many of those
who searched about killing actually did it.But should the police feel obligated to act when such searches are
conducted, if they could be alerted to them?
this, he writes: “We have to be very cautious using search data to predict
crimes at an individual level. The data clearly tells us that there are many,
many horrifying searches that rarely lead to horrible actions. And there has
been, as of yet, no proof that the government can predict a particular horrible
action, with high probability just from examining these searches.So we have to be really cautious about
allowing the government to intervene at the individual level based on search
what do we learn?
say they want or do something, but don’t consistently act in accordance with
those desires or stated actions.
learn that people deceive others and themselves, that they share embarrassing
information to Google about sexless marriages, mental health issues,
insecurities, and animosity toward black people.The author concludes, on a positive note, the
analyzing anonymous and aggregate data, we may all understand that we’re not the
only ones who find marriage, and life, difficult.The second benefit of digital truth serum is
that it alerts us to people who are suffering…The final – and I think, most
powerful-value in this digital truth serum is indeed its ability to lead us
from problems to solutions.With more
understanding, we might find ways to reduce the world’s supply of nasty
future of data science is bright but complicated.Who has access to which data – and how that
data is interpreted – will lead to significant changes in policy and
commerce.A combination of data can
dramatically improve our understanding of the world or commit us down the wrong
author predicts a revolution based on the revelations of Big Data but cautions
us to still rely on other methods to figure out what’s true vs. lie, and what
needs to be done with this knowledge.Otherwise we just govern based on the numbers.
wisely says: “Never compare your Google searches to everyone else’s social
to find a way to appeal to the media and consumers, you may need to be more in touch
with what the data really tells us about how people feel, think, view, and
dream – and how they actually act.Our
current assumptions, polls, and statistical studies may not have the complete