Monthly Archives: July 2018

Phil 7.31.18

7:00 – 6:00 ASRC MKT

  • Thinking that I need to forward the opinion dynamics part of the work. How heading differs from position and why that matters
  • Found a nice adversarial herding chart from The Economist: Brexit
  • Why Do People Share Fake News? A Sociotechnical Model of Media Effects
    • Fact-checking sites reflect fundamental misunderstandings about how information circulates online, what function political information plays in social contexts, and how and why people change their political opinions. Fact-checking is in many ways a response to the rapidly changing norms and practices of journalism, news gathering, and public debate. In other words, fact-checking best resembles a movement for reform within journalism, particularly in a moment when many journalists and members of the public believe that news coverage of the 2016 election contributed to the loss of Hillary Clinton. However, fact-checking (and another frequently-proposed solution, media literacy) is ineffectual in many cases and, in other cases, may cause people to “double-down” on their incorrect beliefs, producing a backlash effect.
  • Epistemology in the Era of Fake News: An Exploration of Information Verification Behaviors among Social Networking Site Users
    • Fake news has recently garnered increased attention across the world. Digital collaboration technologies now enable individuals to share information at unprecedented rates to advance their own ideologies. Much of this sharing occurs via social networking sites (SNSs), whose members may choose to share information without consideration for its authenticity. This research advances our understanding of information verification behaviors among SNS users in the context of fake news. Grounded in literature on the epistemology of testimony and theoretical perspectives on trust, we develop a news verification behavior research model and test six hypotheses with a survey of active SNS users. The empirical results confirm the significance of all proposed hypotheses. Perceptions of news sharers’ network (perceived cognitive homogeneity, social tie variety, and trust), perceptions of news authors (fake news awareness and perceived media credibility), and innate intentions to share all influence information verification behaviors among SNS members. Theoretical implications, as well as implications for SNS users and designers, are presented in the light of these findings.
  • Working on plan diagram – done
  • Organizing PhD slides. I think I’m getting near finished
  • Walked through slides with Aaron. Need to practice the demo. A lot.

Phil 7.29.18

Bandit Algorithms

  • Is this story true? It may be. The Gittins book was first published in 1989
  • The name comes from the 1950s when Frederick Mosteller and Robert Bush decided to study animal learning and ran trials on mice and then on humans. The mice faced the dilemma of choosing to go left or right, after starting in the bottom of a T-shaped maze, not knowing each time at which end they will find food. To study a similar learning setting in humans, a “two-armed bandit” machine was commissioned where humans could choose to pull either the left or the right arm of the machine, each giving a random payoff with the distribution of payoffs for each arm unknown to the human player.
  • William R. Thompson. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika, 1933.

Phil 7.27.18

Ted Underwood

  • my research is as much about information science as literary criticism. I’m especially interested in applying machine learning to large digital collections
  • Git repo with code for upcoming book: Distant Horizons: Digital Evidence and Literary Change
  • Do topic models warp time?
    • The key observation I wanted to share is just that topic models produce a kind of curved space when applied to long timelines; if you’re measuring distances between individual topic distributions, it may not be safe to assume that your yardstick means the same thing at every point in time. This is not a reason for despair: there are lots of good ways to address the distortion. The mathematics of cosine distance tend to work better if you average the documents first, and then measure the cosine between the averages (or “centroids”).
  • The Historical Significance of Textual Distances
    • Measuring similarity is a basic task in information retrieval, and now often a building-block for more complex arguments about cultural change. But do measures of textual similarity and distance really correspond to evidence about cultural proximity and differentiation? To explore that question empirically, this paper compares textual and social measures of the similarities between genres of English-language fiction. Existing measures of textual similarity (cosine similarity on tf-idf vectors or topic vectors) are also compared to new strategies that use supervised learning to anchor textual measurement in a social context.

7:00 – 8:00 ASRC MKT

  • Continued on slides. I think I have the basics. Need to start looking for pictures
  • Sent response to the SASO folks about who’s presenting what.

9:00 – ASRC IRAD

Phil 7.25.18

7:00 – 3:00 ASRC

  • Send out email with meeting time
  • Rather than excerpts from the talks, do a demo of the relevant bits with conclusions and implications. Get the laptop running all the pieces. That means Python and TF and all the other bits.
  • Submitted tuition expenses
  • Submitted Fall 2018 approval
  • Got SASO travel approval!
  • More DNN study
    • Finished CNNs
    • Working on embeddings and W2V. Thought I’d try it on the laptop, but keras can’t find it’s back end and I’m getting other weird errors. One of the big ones was that I didn’t install tk with python. Here’s the answer from stackoverflow: python_fix
    • And now we’re waiting a very long time for a tf ‘hello world’ to run… But it did!
    • Had to also install pydot and graphviz-2.38.msi. Then add the graphviz bin directory to the path.
    • But now everything runs on the laptop, which will help with the demos!
    • Skipped the GloVe and pre-trained embeddings. Ready to start on DNNs tomorrow.

Phil 7.24.18

7:00 – 3:00 ASRC MKT

    • Finished The Radio in Fascist Italy
      • Philip Cannistraro
      • Journal of European Studies
      • scholars have generally agreed that the control of the mass media by the state is a fundamental prerequisite for the establishment and maintenance of totalitarian dictatorships (pg 127)
      • It is not so widely acknowledged, however, that contemporary totalitarian governments have been largely responsible for the initial growth of the mass media-particularly films and the radio-in their respective countries. (pg 127)
      • In their efforts to expose entire populations to official propaganda, totalitarian regimes encouraged and sponsored the development of the mass media and made them available to every· citizen on a large scale basis. (pg 127)
      • Marconi shrewdly reminded Mussolini that it would be politically wise to place control of the radio in the hands of the state, pointing out the radio’s great potential for propaganda purposes (pg 128)
      • “How many hearts recently beat with emotion when hearing the very voice of the Duce! All this means but one thing: the radio must be extended and extended rapidly. It will contribute much to the general culture of the people” (pg 129)
      • … to insure that EIAR’s programmes conformed to the requirements of the regime’s cultural and political policies. The High Commission included government representatives from each major area of culture: literature, journalism., the fine arts, music, poetry, theatre, and films. The programmes Commission screened the transcripts and plans of all and censored the content of all broadcasts. (pg 130)
      • His broadcast, ‘The Bombardment of Adrianople’, was awaited by the public with great interest and was heralded by critics as the most significant cultural event of the Italian radio.ts Marinetti’s colourful language and emotion-packed presentation blasted un expected life into the Italian radio. His flam.boyant style introduced the concept of the ‘radio personality’ in Fascist Italy, and the success of his talk encouraged those who, like Marinetti himself, hoped to make the radio a new art form. Broadcasts by Marinetti, most of which were lectures on Futurism, continued to be heard on Italian radio each month for more than a decade. (pg 131)
      • The regime quickly recognized the effectiveness of this technique in· arousing listener interest, and it was an easy matter to transfer microphones to mass rallies from where the enthusiastic cheers of the spectators could be heard by radio audiences. (pg 132)
      • The popular announcer Cesare Ferri created the characters ‘Nonno Radio’ (Grandfather Radio) and ‘Zia Radio’ (Aunt Radio), speaking to Italian youth with unprecedented familiarity in terms they easily understood. (pg 132)
      • In order to popular arouse interest in its program.me EIAR sought to stimulate indirect audience participation through public contests for short stories, poems, songs, In and children’s fairy tales. addition, surveys were conducted among listeners to discover trends in popular taste. (pg 133)
      • The radio had an important task to fulfil in the totalitarian state, that of binding the Italians together into one nation through common ideals and a common cultural experience inspired by Fascism. (pg 134)
      • Mussolini proclaimed Radio Rurale a great achievement of the Fascist revolution, for contemporary observers saw it as a new instrument with which to integrate rural existence into the mainstream. of national life. (pg 135)
      • The measures taken by the regime to overcome cultural and political provincialism by creating a mass radio audience in the countryside met with qualified success. (pg 137)
      • Regarded by many as an important step towards the creation of a truly popular culture, Radio Btdilla’s purpose was to give the working classes of the city and the countryside the means of acquiring a radio at a modest cost. Through the radio art, instruction, music, poetry-all the cultural masterworks–cease to become the privilege and unjust monopoly of a few elitist groups’. (pg 139)
      • ‘The ministry, in carrying out its delicate functions of vigilance over radio broadcasting, must guide itself by criteria that are essentially of a political and cultural nature.’ (pg 140)
      • Once the radio had been integrated into the structure of the Ministry of Popular Culture, the Fascists began to develop m.ore effective ways of using broadcasting as a cultural medium. While the number and variety of programmes had begun to increase by the beginning of the decade, it was only after 1934 that they became politically sophisticated. (pg 141)
      • Fascist racial doctrines became a major theme of radio propaganda during World War II. An Italo-German accord signed in 1940 to co-ordinate radio propaganda between the two countries included measures to ‘intensify anti-Jewish propaganda’ on the Italian radio as well as in foreign broadcasts.78 The Inspectorate for Radio Broadcasting organized an important series of anti-Semitic prograrnm.es that centred around the ‘Protocols of Zion’, and talks such as ‘Judaism. versus Western Culture’, the ‘Jewish International’, and ‘Judaism. Wanted this War’, were broadcast from 1941 to 1943. (pg 143)
      • information received from the Vatican radio during World War II was generally regarded more accurate than the obvious propaganda broadcasts of the Allies (pg 147)
      • On the radio he astutely employed direct, forceful language, shouting short and vivid sentences to create a sense of drama and arouse emotional reactions. ‘This ‘maniera forte’ that characterized Appelius’ radio talks had a great appeal for many Italians, especially for the ‘little man’ who wanted to be talked to on his own level in terms he could readily understand.121 In his broadcasts Appelius screamed insults and ranted and raved at the foul enemies of Fascism. with a powerful barrage of verbal abuse, inciting his audiences to unmitigated hatred and scorn against the evil ‘anglo-sassoni’ and their allies. (pg 150)
      • In the broad context of Fascist cultural aspirations, all the media aimed at similar goals: the diffusion of standard images and themes that reflected the ideological values of Fascism.; the creation of a mass culture that conformed the needs of the Fascist state in its capacity as a totalitarian to government. (pg 154)
    • Next on the list, Radio: The Intimate Medium
      • Lou Orfanella
      • Radio has always had a special power. It has exerted this power from our grandparents gathered in the living room to listen to an FDR fireside chat as it crackled from a big wooden cabinet filled with glass tubes to our own summer nights of making out as Wolfman Jack howled through the dashboard speakers. There is an intimacy, a one-to-one connection that no other medium can match. (pg 53)
      • “I’m the guy that gets up with them in the morning. I’m in the shower with them, I go to work with them. It is a very intimate time.” (pg 53)
      • Something emergent in talk radio:
        • As Dan Ingram explains: “I felt they were making a major mistake, and for over fifteen years, WABC had ratings around one-point- something, until the conservative, fascist talk shows began to draw the same kind of audience that must have turned out for the spectacle of seeing someone stoned to death in Biblical times.” (pg 54)
        • Bruce Morrow, who still draws high ratings with his broadcasts over WCBS-FM, feels that “People listen because somewhere along the line, Top Forty radio became the closest thing we ever had to a national personality. Rock ‘n’ Roll became the nearest thing we’ve had to an American voice” (pg 55) – Pop culture as dimension reduction/polarization/consensus?
    • From Incivility to Outrage: Political Discourse in Blogs, Talk Radio, and Cable News
      • Sarah Sobieraj and Jeffrey M. Berry
      • Political Communication
      • The country appears to be moving toward a parliamentary-type legislature with the party in power ruling and the party out of power biding its time and doing its best to bring down its opponents. It strains credulity to believe that the new and expanded ideological media has had nothing to do with this trend. For those media commentators outside of mainstream news organizations, the red meat is good versus evil and heroes working at great odds against powerful villains. This favors the most ideological within parties, helping them raise money and gain votes in primaries when they oppose more moderate candidates (pg 36)
    • Continue on SASO slides
    • More LSTM
    • To get a level of visualization from Keras, I had to download graphviz from here, and then add the C:\Program Files (x86)\Graphviz2.38\bin directory to the path and restart Intellij. But now I have pix of the network! model

 

  • Might need to help Aaron out putting together GUI code. Did manage to get everything up and running on my local machine.
  • DOJ CATS slide walkthrough. Found the schema for the DB?
  • 3:30 Meeting with Don to discuss LSTM and topic identification. It occurs to me that this could be the paper that allows me to end the PHD by pointing out the way that JuryRoom would build maps. Possible UIST or DIS paper if framed this way?
    • Meeting went well, though we never got to the dance my PhD parts. Don suggests starting with simple statistical analysis on bag-of-words or tf-idf text
    • Don then introduced me to Aaron Mannes, and we had a nice chat about navigating belief spaces and radicalization. He also suggested looking at qntfy.com.
      • Qntfy is a technology solutions provider bridging data science and human behavior. We make complex psychological and behavioral data accessible, scalable and actionable for both individuals and organizations.

Phil 7.23.18

7:00 – ASRC MKT

  • Starting on the SASO slides. Found my diversity injection slide story:
    • Max Hawkins
      • (From NPR’s Invisibilia) “I just started thinking about these loops that we get into,” he says. “And about how the structure of your life … completely determines what happens in it.” Max’s once beautiful routine suddenly seemed unfulfilling. He felt like he was growing closer to people in his own bubble and becoming isolated from those outside of it. “There was something … that just made me feel trapped,” he says. “Like I was reading a story that I’d read before or I was playing out someone else’s script.” As any computer developer would do, Max turned to technology to craft his way out — a series of randomization applications.
    • Reading Review: Totalitarianism: The Revised Standard Version
      • …they have chosen to identify totalitarianism in terms of a set of six interrelated traits or characteristics-Fried- rich’s oft-referred-to “totalitarian syndrome” (9-io).25 The syndrome includes an official ideology (orientation), a single party typically led by one man (dimension reduction), a terroristic police (herding), a communications monopoly (social influence horizon), a weapons monopoly (??) and a centrally directed economy (dimension reduction)
  • Continued to spin up on LSTM effort. Got my dev environment COMPLETELY up to date. Continued with Deep learning & Keras

3:00 – 5:00 Fika & meeting with Wayne

  • Worked on the slides for PhD status. I realize that this is actually a good time to have demos with conclusions.
  • Talked about options if IRAD falls through
  • Need to think about what are the best ways for the work to have impact

Phil 7.22.18

Modeling relatedness and demography in social evolution

  • With any theoretical model, the modeler must decide what kinds of detail to include and which simplifying assumptions to make. It could be assumed that models that include more detail are better, or more correct. However, no model is a perfect description of reality and the relative advantage of different levels of detail depends on the model’s empirical purpose. We consider the specific case of how relatedness is modeled in the field of social evolution. Different types of model either leave relatedness as an independent parameter (open models), or include detail for how demography and life cycle determine relatedness (closed models). We exploit the social evolution literature, especially work on the evolution of cooperation, to analyze how useful these different approaches have been in explaining the natural world. We find that each approach has been successful in different areas of research, and that more demographic detail is not always the most empirically useful strategy.

Phil 7.20.18

Listening to We Can’t Talk Anymore? Understanding the Structural Roots of Partisan Polarization and the Decline of Democratic Discourse in 21st Century America. Very Tajfel

  • David Peritz
  • Political polarization, accompanied by negative partisanship, are striking features of the current political landscape. Perhaps these trends were originally confined to politicians and the media, but we recently reached the point where the majority of Americans report they would consider it more objectionable if their children married across party lines than if they married someone of another faith. Where did this polarization come from? And what it is doing to American democracy, which is housed in institutions that were framed to encourage open deliberation, compromise and consensus formation? In this talk, Professor David Peritz will examine some of the deeper forces in the American economy, the public sphere and media, political institutions, and even moral psychology that best seem to account for the recent rise in popular polarization.

Sent out a Doodle to nail down the time for the PhD review

Went looking for something that talks about the cognitive load for TIT-FOR-TAT in the Iterated Prisoner’s Dilemma and can’t find anything. Did find this though, that is kind of interesting: New tack wins prisoner’s dilemma. It’s a collective intelligence approach:

  • Teams could submit multiple strategies, or players, and the Southampton team submitted 60 programs. These, Jennings explained, were all slight variations on a theme and were designed to execute a known series of five to 10 moves by which they could recognize each other. Once two Southampton players recognized each other, they were designed to immediately assume “master and slave” roles – one would sacrifice itself so the other could win repeatedly.
  • Nick Jennings
    • Professor Jennings is an internationally-recognized authority in the areas of artificial intelligence, autonomous systems, cybersecurity and agent-based computing. His research covers both the science and the engineering of intelligent systems. He has undertaken fundamental research on automated bargaining, mechanism design, trust and reputation, coalition formation, human-agent collectives and crowd sourcing. He has also pioneered the application of multi-agent technology; developing real-world systems in domains such as business process management, smart energy systems, sensor networks, disaster response, telecommunications, citizen science and defence.
  • Sarvapali D. (Gopal) Ramchurn
    • I am a Professor of Artificial Intelligence in the Agents, Interaction, and Complexity Group (AIC), in the department of Electronics and Computer Science, at the University of Southampton and Chief Scientist for North Star, an AI startup.  I am also the director of the newly created Centre for Machine Intelligence.  I am interested in the development of autonomous agents and multi-agent systems and their application to Cyber Physical Systems (CPS) such as smart energy systems, the Internet of Things (IoT), and disaster response. My research combines a number of techniques from Machine learning, AI, Game theory, and HCI.

7:00 – 4:30 ASRC MKT

  • SASO Travel request
  • SASO Hotel – done! Aaaaand I booked for August rather than September. Sent a note to try and fix using their form. If nothing by COB try email.
  • Potential DME repair?
  • Starting Deep Learning with Keras. Done with chapter one
  • Two seedbank lstm text examples:
    • Generate Shakespeare using tf.keras
      • This notebook demonstrates how to generate text using an RNN with tf.keras and eager execution.This notebook is an end-to-end example. When you run it, it will download a dataset of Shakespeare’s writing. The notebook will then train a model, and use it to generate sample output.
    • CharRNN
      • This notebook will let you input a file containing the text you want your generator to mimic, train your model, see the results, and save it for future use all in one page.

 

Phil 7.19.18

7:00 – 3:00 ASRC MKT

  • More on augmented athletics: Pinarello Nytro electric road bike review m2_0229_670
  • WhatsApp Research Awards for Social Science and Misinformation ($50k – Applications are due by August 12, 2018, 11:59pm PST)
  • Setting up meeting with Don for 3:30 Tuesday the 24th. He also gave me some nice leads on potential people for Dance my PhD:
    • Dr. Linda Dusman
      • Linda Dusman’s compositions and sonic art explore the richness of contemporary life, from the personal to the political. Her work has been awarded by the International Alliance for Women in Music, Meet the Composer, the Swiss Women’s Music Forum, the American Composers Forum, the International Electroacoustic Music Festival of Sao Paulo, Brazil, the Ucross Foundation, and the State of Maryland in 2004, 2006, and 2011 (in both the Music: Composition and the Visual Arts: Media categories). In 2009 she was honored as a Mid- Atlantic Arts Foundation Fellow for a residency at the Virginia Center for the Creative Arts. She was invited to serve as composer in residence at the New England Conservatory’s Summer Institute for Contemporary Piano in 2003. In the fall of 2006 Dr. Dusman was a Visiting Professor at the Conservatorio di musica “G. Nicolini” in Piacenza, Italy, and while there also lectured at the Conservatorio di musica “G. Verdi” in Milano. She recently received a Maryland Innovation Initiative grant for her development of Octava, a real-time program note system (octavaonline.com).
    • Doug Hamby
      • A choreographer who specializes in works created in collaboration with dancers, composers, visual artists and engineers. Before coming to UMBC he performed in several New York dance companies including the Martha Graham Dance Company and Doug Hamby Dance. He is the co-artistic director of Baltimore Dance Project, a professional dance company in residence at UMBC. Hamby’s work has been presented in New York City at Lincoln Center Out-of-Doors, Riverside Dance Festival, New York International Fringe Festival and in Brooklyn’s Prospect Park. His work has also been seen at Fringe Festivals in Philadelphia, Edinburgh, Scotland and Vancouver, British Columbia, as well as in Alaska. He has received choreography awards from the National Endowment for the Arts, Maryland State Arts Council, New York State Council for the Arts, Arts Council of Montgomery County, and the Baltimore Mayor’s Advisory Committee on Arts and Culture. He has appeared on national television as a giant slice of American Cheese.
  • Sent out a note with dates and agenda to the committee for the PhD review thing. Thom can open up August 6th
  • Continuing extraction of seed terms for the sentence generation. And it looks like my tasking for next sprint will be to put together a nice framework for plugging in predictive patterns systems like LSTM and multi-layer perceptrons.
  • This seems to be working: 
    agentRelationships GreenFlockSh_1
	 sampleData 0.0
		 cell cell_[4, 6]
		 influences AGENT
			 influence GreenFlockSh_0 val =  0.8778825396520958
			 influence GreenFlockSh_2 val =  0.8859173062045552
			 influence GreenFlockSh_3 val =  0.9390368569108515
			 influence GreenFlockSh_4 val =  0.9774328763377834
		 influences SOURCE
			 influence UL_point val =  0.032906293611796644
  • Sprint planning
    • VP-613: Develop general TensorFlow/Keras NN format
      • LSTM
      • MLP
      • CNN
    • VP-616: SASO Preparation
      • Slides
      • Poster
      • Demo

 

Phil 7.18.18

divylmzuyaeqjbk

“There was no colusion“…”Anyone involved in that meddling to justice.“

Premises for Data Science Magical Realism

  • What follows are some premises for data science magical realism stories based (very, very loosely) on experiences I’ve had or heard about — premises, that is, for stories about impossible, absurd, magical things happening to data scientists in ordinary data science situations. Enjoy!
  • More from David Masad

Program Synthesis in 2017-18

  • A high-level overview of the recent ideas and representative papers in program synthesis as of mid-2018.
  • Alex (Oleksandr) Polozov, a researcher in the Deep Procedural Intelligence group at Microsoft Research AI, Redmond. I work on neural program synthesis from input-output examples and natural language, intersections of machine learning and software engineering, and neuro-symbolic architectures. I am particularly interested in combining neural and symbolic techniques to tackle the next generation of AI problems, including program synthesis, planning, and reasoning.

UMAP Uniform Manifold Approximation and Projection for Dimension Reduction | SciPy 2018 |(video) (paper)

  • UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction. UMAP is constructed from a theoretical framework based in Riemannian geometry and algebraic topology. The result is a practical scalable algorithm that applies to real world data. The UMAP algorithm is competitive with t-SNE for visualization quality, and arguably preserves more of the global structure with superior run time performance. Furthermore, UMAP as described has no computational restrictions on embedding dimension, making it viable as a general purpose dimension reduction technique for machine learning.
  • This could be nice for building maps

7:00 – 5:00 ASRC MKT

  • Progress on getting my keys back!
  • Got everyone’s response on the Doodle, but only 4 of the 5 line up…
  • Finish first pass through PhD review slides
  • Start SASO slides and poster?
  • Continue with exporting terms from the sim and importing them into python. One of the things that will matter is the tagging of the data with the seed terms from the sim as well as the cell name so that reconstructions can be compared for accuracy.
  • Added the cell location to each <sampleData> so that there can be some kind of tagging/ground truth about the maps we’re inferring.
  • Working on iterating through the etree hierarchy. I can now read in the file, parse it and get elements that I’m looking for.
  • Tomorrow will be pulling the seed words out of the code in an ordered list. Generated sentences will need to be timestamped to that conversations can be reconstructed. That being said, it could be interesting to take seed words out of a generated sentence and add them to the embedding seed words. Something to think about.

Phil 7.17.18

I wrote up some thoughts about Trump’s press conference with Putin.

7:00 – 4:30 ASRC MKT

  • Still can’t connect to the Service center (Betriebsdienst Zentrum) at Zurich U. Tried pinging the conference organizer, who appears to be based on the campus – done. And some progress!
  • Travel report for SASO – done
  • Hotel in Trento – wait till tomorrow.
  • Ping Aaron M. about Doodle – Done
  • Set up meeting with Don – done
  • Start on slides – started

Phil 7.16.18

Vacation is over. Here are some pix

7:00 – 3:00 ASRC MKT

  • No problem logging into timesheet or email from the US. Odd.
  • Expense Report. Bring Receipts!
  • Call Zurich about keys – called. No one there today, call tomorrow before 9:00 +41 44 634 03 09
  • Get hotel in Trento

3:00 – 6:00 Fika, then meeting with Wayne

  • Schedule a meeting with Don to discuss LSTM agent text, and composer/choreographer for Dance my PhD
  • Put together a proposal for the mid-PhD that includes
    • Current work
    • LSTM next step
    • The Wayne Problem
      • Keep the committee as is (defend summer of 2019)
      • Adjust committee (who becomes co-chair?)
    • What to do about JuryRoom
      • Make it post-PhD work
      • Build an instantiation of the theory, but don’t do anything with it (unpublishable, but next steps would be)
      • Build a low-fi version of the website for lab testing
      • Build a 1,000 – 10,000 user version (MySQL, PHP, Angular)
      • Build a 10,000 – 1,000,000 user version
      • Build a fully scaled version

phil 7.12.18

Stampede thinking:

  • Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning
    • Gordon Pennycook
    • David Rand
    • Why do people believe blatantly inaccurate news headlines (“fake news”)? Do we use our reasoning abilities to convince ourselves that statements that align with our ideology are true, or does reasoning allow us to effectively differentiate fake from real regardless of political ideology? Here we test these competing accounts in two studies (total N = 3446 Mechanical Turk workers) by using the Cognitive Reflection Test (CRT) as a measure of the propensity to engage in analytical reasoning. We find that CRT performance is negatively correlated with the perceived accuracy of fake news, and positively correlated with the ability to discern fake news from real news – even for headlines that align with individuals’ political ideology. Moreover, overall discernment was actually better for ideologically aligned headlines than for misaligned headlines. Finally, a headline-level analysis finds that CRT is negatively correlated with perceived accuracy of relatively implausible (primarily fake) headlines, and positively correlated with perceived accuracy of relatively plausible (primarily real) headlines. In contrast, the correlation between CRT and perceived accuracy is unrelated to how closely the headline aligns with the participant’s ideology. Thus, we conclude that analytic thinking is used to assess the plausibility of headlines, regardless of whether the stories are consistent or inconsistent with one’s political ideology. Our findings therefore suggest that susceptibility to fake news is driven more by lazy thinking than it is by partisan bias per se – a finding that opens potential avenues for fighting fake news.

From Alessandro Bozzon (Scholar):

  • I am Assistant Professor with the Web Information Systemsgroup, at the Delft University of Technology. I am Research Fellow at the AMS Amsterdam Institute for Advanced Metropolitan Solutions, and a Faculty Fellow with the IBM Benelux Center of Advanced Studies.

    My research lies at the intersection of crowdsourcing, user modeling, and web information retrieval. I study and build novel Social Data science methods and tools that combine the cognitive and reasoning abilities of individuals and crowds, with the computational powers of machines, and the value of big amounts of heterogeneous data.

    I am currently active in three investigation lines related to Social Data Science: Intelligent Cities (SocialGlass; Crowdsourced Knowledge Creation in Online Social Communities (SEALINCMedia COMMIT/, StackOverflow); and Enterprise Crowdsourcing (with IBM Benelux CAS).

  • Modeling CrowdSourcing Scenarios in Socially-Enabled Human Computation Applications
    • User models have been defined since the 1980s, mainly for the purpose of building context-based, user-adaptive applications. However, the advent of social networked media, serious games, and crowdsourcing/human computation platforms calls for a more pervasive notion of user model, capable of representing the multiple facets of social users and performers, including their social ties, interests, capabilities, activity history, and topical affinities. In this paper, we define a comprehensive model able to cater for all the aspects relevant for applications involving social networks and human computation; we capitalize on existing social user models and content description models, enhancing them with novel models for human computation and gaming activities representation. Finally, we report on our experiences in adopting the proposed model in the design and implementation of three socially enabled human computation platforms.
  • Sparrows and Owls: Characterisation of Expert Behaviour in StackOverflow
    • Question Answering platforms are becoming an important repository of crowd-generated knowledge. In these systems a relatively small subset of users is responsible for the majority of the contributions, and ultimately, for the success of the Q/A system itself. However, due to built-in incentivization mechanisms, standard expert identification methods often misclassify very active users for knowledgable ones, and misjudge activeness for expertise. This paper contributes a novel metric for expert identification, which provides a better characterisation of users’ expertise by focusing on the quality of their contributions. We identify two classes of relevant users, namely sparrows and owls, and we describe several behavioural properties in the context of the StackOverflow Q/A system. Our results contribute new insights to the study of expert behaviour in Q/A platforms, that are relevant to a variety of contexts and applications.