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Examining Gender and Power on Wikipedia Through Face and Politeness

Soubki, Adil, Choi, Shyne, Rambow, Owen

arXiv.org Artificial Intelligence

We propose a framework for analyzing discourse by combining two interdependent concepts from sociolinguistic theory: face acts and politeness. While politeness has robust existing tools and data, face acts are less resourced. We introduce a new corpus created by annotating Wikipedia talk pages with face acts and we use this to train a face act tagger. We then employ our framework to study how face and politeness interact with gender and power in discussions between Wikipedia editors. Among other findings, we observe that female Wikipedians are not only more polite, which is consistent with prior studies, but that this difference corresponds with significantly more language directed at humbling aspects of their own face. Interestingly, the distinction nearly vanishes once limiting to editors with administrative power.


Intention and Face in Dialog

Soubki, Adil, Rambow, Owen

arXiv.org Artificial Intelligence

The notion of face described by Brown and Levinson (1987) has been studied in great detail, but a critical aspect of the framework, that which focuses on how intentions mediate the planning of turns which impose upon face, has received far less attention. We present an analysis of three computational systems trained for classifying both intention and politeness, focusing on how the former influences the latter. In politeness theory, agents attend to the desire to have their wants appreciated (positive face), and a complementary desire to act unimpeded and maintain freedom (negative face). Similar to speech acts, utterances can perform so-called face acts which can either raise or threaten the positive or negative face of the speaker or hearer. We begin by using an existing corpus to train a model which classifies face acts, achieving a new SoTA in the process. We then observe that every face act has an underlying intention that motivates it and perform additional experiments integrating dialog act annotations to provide these intentions by proxy. Our analysis finds that dialog acts improve performance on face act detection for minority classes and points to a close relationship between aspects of face and intent.


Kamala, Dems talk about Trump 'weaponizing' DOJ. But guess who got there first?

FOX News

Vice President Kamala Harris recently warned donors in San Diego that Donald Trump has "threatened to weaponize the Department of Justice against his political enemies" if elected. Does our clueless vice president not get that half the country believes the Biden-Harris White House has been doing exactly that for over three years? While Joe Biden prattles on about threats to democracy, his Department of Justice has created the ultimate threat to democracy -- ruthlessly waging war on MAGA Republicans, Catholics, pro-life advocates, parents' groups -- anyone and everyone who does not buy into their progressive agenda. It is not just the outrageous legal persecution of the former president – the four dubious cases brought against Trump, each less credible than the last. It is not just Trump's conviction on flimsy charges brought by a politically-motivated district attorney and overseen by a clearly conflicted judge. DOJ CLAIMS IT CAN'T RELEASE BIDEN-HUR INTERVIEW DUE TO THREAT OF AI DEEPFAKES It is also the pursuit and prosecution of Trump allies including Peter Navarro, Roger Stone, Paul Manafort, Rick Gates, George Papadopoulos, Allen Weisselberg and Steve Bannon, all of whom have been sentenced to time in prison.