Interaction Dynamics and Persuasion Strategies

I recently read Chenhao Tan et al’s 2016 WWW paper Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions, which presents an interesting study of the linguistic features of persuasion.

Coming from a deliberative background, the word ‘persuasion’ has negative connotations. Indeed, Habermas and others strongly argue that deliberation must be free from persuasion – defined roughly as an act of power that causes an artificial opinion change.

In its more colloquial sense, however, persuasion needn’t be so negatively defined. Within the computer science literature on argument mining and detection, persuasion is generally more benignly considered as any catalyst causing opinion change. If I “persuade” you to take a different route because the road you were planning to take is closed, that persuasion is not problematic in the Habermasian sense as long as I’m not distorting the truth in order to persuade you.

Furthermore, Tan et al gather a very promising data set for this investigation – a corpus of “good faith online discussions” as the title says. Those discussions come from Reddit’s Change My Mind forum, a moderated platform with explicit and enforced norms for sharing reasoned arguments.

Each thread starts with a user who explicit states they want to have their opinion changed. That user then shares said opinion and outlines their reasoning behind the opinion. Other users then present arguments to the contrary. The original poster then has the opportunity to award a “delta” to a response if it succeeded in changing their opinion.

So there’s a lot to like about the structure of the dataset.

I have a lot of questions, though, about the kinds of opinion which are being shared and changed. Looking through the site today, posts cover a mix of serious political discussion, existential crises, and humorous conundrums.

The all time most highly rated post on the site begins with the opinion, “Strange women lying in ponds distributing swords is no basis for a system of government.” So it’s unclear just how much we can infer about debate more broadly from these users.

However, Tan et al, intentionally restrict their analysis to linguistic features, carefully comparing posts which ultimately win a “delta” to the most similar non-delta post responding to the same opinion. In this way, they aim to “de-emphasize what is being said in favor of how it is expressed.” 

There’s a lot we lose, of course, by not considering content, but this paper makes valuable contributions in disambiguating the effects of content from the effects of syntactic style.

Interestingly, they find that persuasive posts – those which earn a delta from the original poster – are more dissimilar for the originating post in content words, while being more similar in stop words (common words such as “a”, “the”, etc). The authors are careful not to make causal claims, but I can’t help but wonder what the causal mechanism behind that might be. The similarity of content words matched by the dissimilarity of stop words seems to imply that users are talking about different things, but in similar ways.

There’s a lot of debate, though, about exactly, what should count as a “stop word” – and whether stop word lists should be specially calibrated for the content. Furthermore, I’m not familiar with any deep theory on the use of stop words, so I’m not sure this content word/stop word disjunction really tells us much at all.

The authors also investigate usage of different word categories – finding, for example, that posts tend to begin and end with tangible arguments while become more abstract in the middle.

Finally, they investigate the features of users who award deltas – e.g., users who do change their mind. In this setting, they find that people who use more first person singular pronouns are more likely to change, while those using more first person plurals are less likely to change. They posit that the first person plural indicates a sort of diffuse sense of responsibility for a view, indicating that the person feels less ownership and is therefore less likely to change.

I’d love to see an extension of this work which dives into the content and examines, for example, what sorts of opinions people are likely to change – but this paper presents a thought-provoking look the persuasive effects of linguistic features themselves.

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Text as Data Conference

At the end of last week, I had the pleasure of attending the eighth annual conference on New Directions in Analyzing Text as Data, hosted by Princeton University and organized by Will Lowe, John Londregan, Marc Ratkovic, and Brandon Stewart.

The conference had a truly excellent program, and was packed with great content on a wide variety of text analysis challenges.

There were a number of papers on topic modeling, including work from my colleague Ryan Gallagher on Anchored correlation explanation: Topic modeling with minimal domain knowledge. – a really cool, information-theory approach to topic modeling.

Luke Miratrix also presented joint work with Angela Fan, Finale Doshi-Velez on Prior matters: simple and general methods for evaluating and improving topic quality in topic modeling, an approach which aims to approve upon standard LDA by using priors to promote informative words.

I also really enjoyed Hanna Wallach’s presentation on A network model for dynamic textual communications with application to government email corpora, which introduces the Interaction-Partition Topic Model (IPTM), which combines elements of LDA with ERGMs.

There were also a number of talks reflecting and improving upon the ways in which we approach the methodological challenges of textual data.

Laura Nelson argued for a process of computational grounded theory, in which textual analysis helps guide and direct deep reading, but in which the researcher stays intimately familiar with her corpus.

Justin Grimmer presented the great paper, How to make causal inferences using texts, which presents a conceptual framework for making causal inference using text.

For my own research, Will Hobbs might get the prize for method I’d most like to use, with his paper on Latent dimensions of attitudes on the Affordable Care Act: An application of stabilized text scaling to open-ended survey responses. He presents a very clever method for scaling common and uncommon words in order to extract latent dimensions from short text. It’s really cool.

And, of course, Nick Beauchamp presented work done jointly with myself and Peter Levine on mapping conceptual networks. In this work, we present and validate a model for measuring the conceptual network an individual uses when reasoning. In these networks, nodes are concepts and edges represent the connections between those concepts More on this in future posts, I’m sure.

Finally the session titles were the absolute best. See, for example:

  • How Does This Open-Ended Question Make You Feel?
  • Fake Pews! (a session on religiosity)
  • America’s Next Top(ic) Model
  • Fwd: Fw: RE: You have to see this paper!

Well played, well played.

Many thanks to all the conference organizers for a truly engaging and informative couple of days.

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Me Too

I woke up this morning to a flood a #MeToo comments, as women from all spectra of my life stepped forward to share their personal stories of sexual abuse and harassment; stories of being silenced, of not being believed, of being told it was their fault, of normalizing the incessant stream of misogyny.

It’s a powerful campaign, and – at least in my feeds – has successfully emphasized how wide-spread these experiences are. Yes, all women have suffered some form of abuse or harassment. All women.

To be honest, it was more than I was prepared to handle on a Monday morning. Of course, I am glad to see these issues gaining mainstream attention, and I’m hopeful that the current wave of shock and indignation will ultimately lead to greatly needed change. But…reading about sexual assault and harassment is not my ideal way to start the day.

I don’t want to think back to remember just how young I was when I was first harassed. 9? 10, maybe? Before then, my memory is too fuzzy to be reliable.

I don’t want to figure out how old I was when strange men regularly took to following me down the street, making comments far too inappropriate to be repeated here. I may as well ask how old I was when I started going out alone – harassment is so indelibly intertwined with the way I experience the world.

And I certainly don’t want to think back to my own stories of assault. Stories I’m barely prepared to whisper privately, much less share publicly. I don’t have energy for that today.

I don’t want to think about such things, and I don’t want to relive such things, except on my own time on my own terms. I’m glad to see so many women empowered to share their stories, and I’m glad to see so many men seeming to take their words seriously. But at the same time, I just want to yell:

YES, OF COURSE, ME TOO.

These experiences happen to all women, and it shouldn’t take a flood of “me too” for us to admit we have a problem. We shouldn’t be forced to relive our traumas, or prove our traumas, or justify our traumas. It shouldn’t be solely on women to fight this battle. We shouldn’t be have to say, “me too.”

Ringing in my ears are the words of Shakespeare’s Desdemona. Shortly before her husband murders her in retribution for imagined infidelity, confronted with increasing abuse and a situation beyond her control, she shakes her head and sighs:

Oh, these men, these men.

Desdemona is caught in a double-bind. She can neither speak up nor stay silent. She is alone and truly powerless to act.

There are so many levels of horror to assault. The act itself is an abuse beyond accounting, but there’s also the fact that many women are assaulted not by some shadowy stranger but someone that they know. Many women are forced to live in contact with their abuser, picking up the pieces of their life as though nothing happened at all. Seeing him succeed in life while leaving behind a restless wake of harassment charges.

Too often, the actions of these abusers are an open secret. Everybody knows. Women try to warn each other off, knowing that open complaints will only result in retribution while doing nothing to harm the assailant. The men know, too. Nothing is done.

And that big nothing only makes it more clear who has the power, who is protected.  Women continue to suffer, surrounded by a sea of men who claim to care but who fail to act.

Scattered in among the “me too” posts have been a number of men offering their support and solidarity. I appreciate many of these. I know a lot of genuinely good men who I’m glad to see in the fight.

But, there’s also another type. As one Twitter personality put it: “ok. its happened. a man who sexually assaulted me has faved another woman’s tweets about calling out harassment and assault.”

I’m hardly surprised. I know some of those men, too.

The problem isn’t a few bad apples who go around assaulting women at the drop of a hat. It isn’t simply about identifying the most virulent harassers and bringing them to justice.

The problem is a culture in which men feel entitled to sexual attention; in which they commit abuse without even knowing it. Or, at least, without the slightest acknowledgement that their actions were problematic.

As long as assault and harassment can be written off as “boys being boys,” as long as it’s a possibility that “she was asking for it,” as long as men fail to call each other out for inappropriate behavior and allow abusive men to go unchallenged amongst us, we will perpetuate a culture of abuse – no matter how many women come forward to share their stories and to say, yes –

Me too.

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On Soap and Apologies

This weekend, Dove soap was forced to pull a Facebook ad which appeared to show a black woman miraculously turning into a white woman as a result, presumably, of the purifying power of their soap.

The full narrative here is, of course, complicated. As Lola Ogunyemi, the black model featured at the top of the ad explains:

There were seven of us in the full version, different races and ages, each of us answering the same question: “If your skin were a wash label, what would it say?”

So, you can see, perhaps, where Dove was hoping to go with this ad. The intended narrative wasn’t about a black woman cleansing herself into a white woman, but about how, despite our seeming differences, we all have skin and therefore all need to buy soap.

It’s not the worst pitch I’ve ever heard.

The problems here, however, are many. The version of the ad which garnered so much attention featured only three women from the apparently diverse cast and began with Ogunyemi transforming into a white model.

This in itself is enough to raise concern. There is, unfortunately, a long history of racism in soap ads. See, for example Cook’s Lighting Soap and Vinonlia Soap. And such problematic advertising isn’t just in the past: in 2011, Dove had to remove another ad which seemed to imply that black skin was “dirty” while white skin was “clean.”

So you can see, perhaps, why the ad caused so much offense.

As Ogunyemi said, “There is a lack of trust here, and I feel the public was justified in their initial outrage.”

And if the ad wasn’t bad enough, I personally was rather disappointed in Dove’s apology:

As a part of a campaign for Dove body wash, a 3-second video clip was posted to the US Facebook page which featured three women of different ethnicities, each removing a t-shirt to reveal the next woman. The short video was intended to convey that Dove body wash is for every woman and be a celebration of diversity, but we got it wrong. It did not represent the diversity of real beauty which is something Dove is passionate about and is core to our beliefs, and it should not have happened. We have removed the post and have not published any other related content. This should not have happened and we are re-evaluating our internal processes for creating and approving content to prevent us making this type of mistake in the future. We apologize deeply and sincerely for the offense that it has caused and do not condone any activity or imagery that insults any audience.

Giving the impression – accidental or not – that you think black skin is dirty goes far beyond “missing the mark.”

As a reformed marketer who used to get homework assignments to write brand apologies in grad school, I’ve been thinking about what kind of apology I would have penned.

The problem, I think, with the actual apology, is that it tries too hard to remain neutral. It is seeped in meaningless, corporate language that comes off as insincere and primarily aimed at minimizing PR damage. It doesn’t really say “we care” so much as it says, “please don’t stop buying our products.”

In some senses, this is a wise strategic maneuver. Politics of any kind has long been considered the third rail of advertising, and conventional wisdom says that political stances should be avoided at any cost.

The problem is, that doesn’t work in a world where everything is political. It doesn’t work in a world where failing to say anything isn’t neutral, but tacitly complicit. In world where black men are being murdered in the street and incarcerated at alarming rates, you can’t respond to concerns of racism with a shruggie and an “our bad.” If you want to apologize, you need to do more than that.

Interesting, another story in the headlines this weekend came from the NFL, where Vice President Pence walked out of a game after some players knelt during the national anthem. Afterwards, I was struck by the statement of 49ers player Eric Reid:

This is what systemic oppression looks like – a man with power comes to the game, tweets a couple things out and leaves the game with an attempt to thwart our efforts.  

And in many ways, that’s what the Dove ad – and the inevitable “racist or not?” debate that followed – comes down to.

This is what systemic oppression looks like.

It’s not Dove’s fault they made an ad that was interpreted as racist. It is the collective fault of a society in which white is implicitly assumed to mean better. Of a society in which certain perspectives and narratives are constantly and consistently marginalized and pushed out of the collective consciousness. How many people of color worked on that Dove ad, do you think? How many people of color were involved in the concept? In the editing?

The ad isn’t the disease, it is a symptom.

As I’ve been thinking about it, I’ve become even more disappointed that Dove didn’t take advantage of the opportunity. That they didn’t apologize more fully and meaningfully. The ad was problematic, sure, but if they were serious about being a bastion of diversity, the mistake also set them up for heroism.

They could have come out so strong on this, could have come out acknowledging that they failed – that we all fail, because we’re embedded in a system of white supremacy where it’s easy, from a position of privilege, to miss the offense you can cause. Because no advertisement has ever implied that “people like you” are dirty, it never crossed your team’s mind that this could be a concern.

They could have said that they’re doing their best to unlearn harmful social norms, to educate themselves to do better in the future. They could have said that mistakes are inevitable, and they appreciate people calling them out when they happen. They could have said that we’re all a little bit racist because we live in a racist society. They could have said they’re doing their best to change that, to fight against it every day.

They could have said so much in their apology. They could have said so much more than a half-hearted “missed the mark.” They could have – and they should have. That’s what I would recommend if I were on Dove’s PR team.

Of course – this may be the reason I don’t work in corporate advertising.

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Title VII

Yesterday, Attorney General Jeff Sessions sent a memo to agency heads and US attorneys. Obtained by BuzzFeed, the memo read in part:

Title VII’s prohibition on sex discrimination encompasses discrimination between men and women but does not encompass discrimination based on gender identity per se, including transgender status.

In other words, while federal law previously recognized that Title VII of the 1964 Civil Rights Act applied to all forms of gender discrimination, the Justice Department is now choosing to interpret the law more narrowly; no longer protecting all men and women from employer, voting, or other forms of public discrimination. Specifically, transgender men and women will no longer have these federal protections.

Currently, only 20 states plus the District of Columbia have laws prohibiting discrimination against transgender individuals. So with the distribution of a memo, three fifths of our nation’s citizens just lost human rights protections which they had the day before.

It shouldn’t be that easy to take away basic rights.

Additionally, the removal of federal backing puts existing state laws into greater peril, as opponents are already mobilized trying to over turn state laws. Even more of our citizens could lose their rights.

This unconscionable act cannot go unchallenged.

In his memo, Session tries to sound nonchalant about stripping citizens of their rights. The new Justice Department interpretation is “a conclusion of law, not policy. As a law enforcement agency, the Department of Justice must interpret Title VII as written by Congress.”

Scapegoating Congress for this egregious interpretation, however, flies in the face of existing case law and existing understanding Title VII protections.

Sessions attempts to appear all innocent and neutral in re-interpreting this law:

The Justice Department must and will continue to affirm the dignity of all people, including transgender individuals. Nothing in this memorandum should be construed to condone mistreatment on the basis of gender identity, or to express a policy view on whether Congress should amend Title VII to provide different or additional protections.

But it’s not neutral to roll back protections which have been in place, and it’s not innocent to explicitly remove protections covering transgender individuals. Despite his claims to the contrary, this is a policy move, not a legal one.

Furthermore this move comes just days after the United States took a position – as just one of 13 countries – against a UN resolution condemning the death penalty as a sanction for same-sex relations.

Yes, you read that right – we are no longer against the state-sanction murder of people for being gay.

The current administration is waging a war against human rights on many fronts. I know we are tired, we are exhausted and numbed from the constant stream of negative news. But we cannot allow these policy changes to pass silently or without confrontation.

We cannot let it be okay to simply re-interpret someone’s rights away.

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Automated Methods for Identifying Civilians Killed by Police

I recently read Keith et al’s excellent paper, Identifying civilians killed by police with distantly supervised entity-event extraction, which was presented this year at the conference on Empirical Methods on Natural Language Processing, or, as it’s more commonly known, EMNLP.

The authors present an initial framework for tackling an important real world question: how can you automatically extract from a news corpus the names of civilians killed by police officers? Their study focuses on the U.S. context, where there are no complete federal records of such killings.

Filling this gap, human rights organizations and journalists have attempted to compile such a list through the arduous – and emotionally draining – task of reading millions of news articles to identify victim names and event details.

Given the salience of this problem, a Keith et al set out to develop a more streamlined solution.

The event-extraction problem is furthermore an interesting NLP challenge in itself – there are non-trivial disambiguation problems as well as semantic variability around indicators of civilians killed by police. Common false positives in their automated approaches, for example, include officers killed in the line of duty and non-fatal encounters.

Their approach relies on distant supervision – using existing databases of civilians killed as mention-level labels. They implement this labeling with both “hard” and a “soft” assumption models. The hard labeling assumes that every mention of a person (name and location) from the gold-standard database corresponds to a mention of a police killing. This assumption proves to be too hard and an inaccurate model of the textual input.

The “soft” models perform better. Rather than assume that every relevant sentence corresponds to a mention of a police killing, soft models assume that at least one of the sentences do. That is, if you take all the sentence in the corpus which mention an individual known to have been killed by police, at least one of those sentences directly conveys information of the killing.

Intuitively, this makes sense – while the hard assumption takes every mention of Alton Sterling, Michael Brown, or Philandro Castile to occur in a sentence mentioning a police killing, we know from simply reading the news that some of those sentence will talk about their lives, their families, or the larger context in which their killing took place.

For both assumptions, Keith et al compare performance between a convolutional neural net and a linear regression model – ultimately finding that the regression, with the soft assumption, out performs the neural net.

There’s plenty of room for improvement and future work on their model, but overall, this paper presents a clever NLP application to a critical, real world problem. It’s a great example of the broad and important impact NLP approaches can have.

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White Space

This weekend, I had the opportunity to attend a rich discussion hosted by The Welcome Project with local author Jennifer De Leon. The conversation focused on De Leon’s 2013 short story The White Space.

While helping her father put together his first résumé, the U.S.-born De Leon writes:

Without cell phone or fax numbers, email or website addresses, the top of the page looks lonely. Where do I write that my father grew up along the southern coast of Guatemala, where his father worked for the U.S.-owned United Fruit Company (UFC), which helped kick Communism to the world curb while pretending to care about Guatemalan citizens’ intake of bananas? They were only interested in profits and maintaining a capitalist economy. 

…On my own résumés over the last ten years, phrases like terminal degree, academic honors, and double major are arranged nearly under the canopy of this section. But I can’t use any of these terms here. My father was denied the opportunity to complete secondary school in Guatemala because he needed to help support his brothers and sisters. Instead he plucked feathers off dead chickens in a small factory in Guatemala City from the time he was 14 years old.

…So tonight, as I help my father write his first résumé, I struggle to find words to fill this white space.

There is much in De Leon’s story which would resonate with any adult child: that feeling that you don’t really know your parents the way you might know a friend; that there is something intangibly distant about their experiences; that they lived in and were shaped by a world which ceased to exist before you were born; that the rich texture of their experience will always be beyond your grasp.

There is much in her story which would resonate with any first-generation to college student: feeling that vast void which palpably disconnects generational experience; realizing the values and norms you so blithely take for granted can seem foreign and obscure; coming to the inescapable conclusion that those same norms glibly dismiss the experiences of people whom you know to have real value.

And, as De Leon and others discussed this weekend, there is much in her story which resonates broadly with children of immigrants: feeling the generational and cultural divide even more sharply; feeling ashamed at your lack of fluency in your parent’s language; feeling like you’re torn between selves, between worlds, between identities.

Feeling like nothing you can do will ever make up for the sacrifice your parents made on your behalf.

In reflecting on these all these interwoven, sweet and painful complications, De Leon concluded:

“Like most beautiful things in life, it’s not so simple. I just do my best.”

 

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Crime and Hate

Ally Lee Steinfeld had been missing since early September. Her body was found recently, mutilated and burned. She was 17.

Her death made Steinfeld at least the 21st transgender person killed in the United States this year. A record high of 22 murders were captured by the Human Rights Campaign last year.

We have to do better.

Steinfeld’s case is not being pursued as a hate crime. The sheriff overseeing the case told the Associated Press: “You don’t kill someone if you don’t have hate in your heart. But no, it’s not a hate crime.” That talking point was echoed by the prosecutor in the case, who told Time: “I would say murder in the first-degree is all that matters. That is a hate crime in itself.”

Perhaps this is accurate in a practical sense – in Missouri, where the crime took place, first-degree murder is punishable by execution or life imprisonment. A hate crime charge would be unlikely to add penalty.

Such comments, however, miss the point. A woman is dead. We have to do better.

Some advocates have even started to question whether hate crimes prosecution is an effective strategy. As one ACLU lawyer put it, “I worry that what hate crime laws do is narrow our focus on certain types of individual violence while absolving the entire system that generates the violence.”

And that’s the thing – it is a problem with the entire system. We are all culpable in perpetuating the gross transphobia of our society – through violent transphobic acts, through subtle jokes and misgendering, or by being complicit through silence while such hateful acts take place.

We have to do better.

Personally, I’m not prepared to abandon hate crime legislation just yet – whether adding to a punishment or not, ignoring the hate of a crime seems to implicitly indicate that while the crime may be punishable, the hate itself is sanctioned. But I’ve met a lot of good, smart lawyers who tell me that sometimes you have to sacrifice framing in the legal system – you go for the toughest penalty you can go for.

I do not know whether we can best accomplish our work through hate crime legislation or through other modes of advocacy. I only know that we have to do better.

We tell young women that they can be anything, that they can do anything. That they should shut down the haters and embrace their true selves. We tell women that it is their right in the 21st century to be the person they want to be. We tell them this is America. We tell them they are free.

Three months before she died, Steinfeld posted to Instagram: “I am proud to be me I am proud to be trans I am beautiful I don’t care what people think.”

We have to do better.

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A Living Language

Languages which are still being spoken are generally referred to as living languages. The metaphor is apt – languages are “living” not only insofar as its speakers are biologically living, but in that the language itself grows and changes throughout time. In a genuinely meaningful sense of the word, the language is alive.

This is a beautiful metaphor, but problematic for text analysis. It is, after all, difficult to model something which is changing while you observe it.

Language drift can be particularly problematic for digital humanities projects with corpora spanning a century or more. As Ben Schmidt has pointed out, topic models trained on such corpora produce topics which are not stable over time – e.g. a single topic represents different or drifting concept during different windows of time.

But the changes of a language are not restricted to such vast time scales. On social media and other online platforms, words and meanings come and go, sometimes quite rapidly. Indeed, there’s no a priori reason to think such rapid change isn’t a feature of all every day language – it is simply better documented through digital records.

This raises interesting questions and problems for scholars doing text analysis – at what time scales do you need to worry about language change? What does language change indicate for an individual or for a society?

One particularly interesting paper which tackles some of these questions is Danescu-Niculescu-Mizil et al’s No country for old members: User lifecycle and linguistic change in online communities.

Studying users of two online beer discussion forums, they find remarkably that users have a consistent life cycle – new users adopt the language of the community, getting closer and closer to linguistic norms. At a certain point, however, their similarity peaks – users cease changing with the community and move further and further linguistically as a result.

The language of the community continues changing, but the language of these “older” users does not.

This finding is reminiscent of earlier studies on organizational learning, such as those by James March – in which employees learn from an organization while the organization simultaneously learns from the employees. In his simulations, organizations in which people learn too quickly fail to converge on optimal information. Organizations in which people learn more slowly – or in which employees come and go – ultimately converge on better solutions.

Both these findings reflect the sociolinguistic theory of adult language stability – the idea that your learning, and specifically your language stays steady after a certain age. The findings from Danescu-Niculescu-Mizil, however, suggests something more interesting: your language becomes stable overtime in a given community. It’s not clear that your overall language will stabilize, rather, you learn the norms of a given community. Since these communities may change overtime, your overall language may still be quite dynamic.

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The Yellow Day

I made the mistake of going outside today, so now all I can think about is how incredibly hot it is. For people who bask in warm weather, I suppose, it is not too miserable – but, for me, upper 80s at the end of September is more that I would hope for.

Mid-60s would do just fine.

If you’re wondering, the average high for Boston in September is a reasonable 73 degrees Fahrenheit. The record high, however, is a discomforting 102, achieved in 1881.

I was curious to learn more about that heat wave – hoping, perhaps, for some eloquently antiquated news paper articles on the subject.

Instead, I found something much more interesting. The record 102 temperature was reached on September 7, 1881 – the day after the “Yellow Day,” when “saffron curtain” mysteriously blanketed New England states.

It was eventually traced back to the great Thumb Fire of Michigan, one of the most devastating fires in that state’s history, burning over a million acres, but at the time, no one had any idea what was going on.

As the Boston Globe described:

Yesterday Boston was shrouded, and nature’s gloom soon infusing itself into the hearts of all made it a day long to be remembered, reminding one vividly of the famous dark day of years ago. About 7 O’Clock in the morning the golden pall shrouded the city in its embrace, and the weird unreal appearance continued throughout the day. As one approached a doorway from within and glanced out upon the sidewalk and street, it was difficult to dispel the illusion that an extensive conflagration was raging near, and that it was the yellow, gleaming light from the burning houses that produced the singular effect. Stepping to the sidewalk and glancing upward the roofs of the houses cut sharp and clear against the depths beyond.

A historian further described the eerie chromatic effects of the smoke:

The air became still, and calm, during that Tuesday, and people remarked about the odd tinge that colors took on as the day wore on.  Plants were particularly brilliant – the odd light sharpening their green and blue hues.  Lawns, usually a mundane green, took on brilliant color, and looked oddly bluish, in the day’s strange light.  Yellow objects appeared colorless and white, and the color in red objects popped, while blue objects became ghostly.  People in the street looked sickly and yellowish.  Overhead, birds flew low in the skies.

The event was particularly startling because professed Prophetess Mother Shipton had reportedly predicted some two centuries before:

The world to an end shall come,
In eighteen hundred and eighty one.

As far as I can tell, however, the world did not actually come to an end that day.

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