《镜子大全》《朝华午拾》分享 http://blog.sciencenet.cn/u/liwei999 曾任红小兵,插队修地球,1991年去国离乡,不知行止。

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Small talk with Daughter on US Election

已有 1817 次阅读 2016-11-15 09:50 |个人分类:立委科普|系统分类:生活其它|关键词:social,media,US,election,sentiment,analysis| Analysis, Social, Election, media, sentiment

just had a small talk with Tanya on US election, she was super angry and there was a big demonstration against Trump in her school too

T:

I don't want him to win
I don't want him to do well
Or else another racist gets elected

Me:

neither did I
IF he does very badly, he will be impeached;
or at least he will not be reelected in 4 years.
But now that he is, we can keep an open mind.
There is an element of sentiment he is representing: so-called silent majority, that is why most polls were wrong.
By the way, many have praised my social media analysis just before the election, mine was way better than all the popular polls such as CNN. This is not by accident, this is power of big data and high tech in the information age:
with deep NLP and social media, we can pick up sentiments way more reliable and statistical than the traditional polls, which usually only call 500 to 1000 for opinions to hope they represent 200 million voters. My mining and analysis are based on millions and millions of data points. So in future we have to utilize and bring the automatic NLP into things like this as one important indicator of insights and public opinions and sentiments

T:

daddy
you're amazing
Your technology is amazing

Me:

I got lots of compliments for that, but yours mean the most to me.
What happened in the election as I had been tracking using our NLP sentiment tool was:
1. Clinton was clearly leading in the period after the recording scandal of Trump and before the FBI started reopening Clinton's email case: Big data mining shows clear social rating decline of Trump last month.
2. Clinton has always been leading in Spanish-speaking communities and media, but that did not seem to be sufficient to help revert the case: Trump sucks in social media big data in Spanish.
3. The event of FBI re-opening the email investigation gave Clinton the most damage: Trump's scandal was cooling down and the attention was all drawn to Clinton's email case so that the sentiment had a sharp drop for Clinton (【社煤挖掘:大数据告诉我们,希拉里选情告急】)
4. When FBI finally reissued a statement that there was no evidence to charge Clinton only 2 days before the election, time was too short to remedy the damage FBI did in their first event of reopening the case: my big data tracking found that there was some help but not as significant (【大数据跟踪美大选每日更新,希拉里成功反击,拉川普下水】).
5. Then just before the election, I did a final update of the big data sentiment tracking for the last 24 hours versus last 3 months, and found that Trump had a clear leading status in public opinion and sentiments, so I decided to let the world know it although at the point most everyone believed that Clinton was almost sure to win.

T:

Oh my god dad your machine is the smartest tracker on the market
Dad your system is genius
This is exactly what media needs
This is amazing
I think this would be the planets smartest machine

Me:

I do not disagree, :=)
It was a tight competition and with good skills, things could turn different in result. In terms of popularity votes, they are too close to be statistically different, so anything at the right timing could have changed the result.
On retrospect, FBI did a terrible thing to mess up with the election:
they reopened a case which they did not know the results just 10 days before the election which made a huge difference. On the other hand, the recording scandal was released too early so that although it hurt Trump severely at the time, yet it allowed FBI to revert the attention to Clinton
In future, there should be a strict law disallowing a government agency, which is neutral politically by nature, to mess up with an election within a time frame, so Trump's winning the case to my mind has 80%+ credit from the FBI events.
What a shame.



[Related]

Final Update of Social Media Sentiment Statistics Before Election




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