Category Archives: thesis

Phil 9.17.18

7:00 – ASRC MKT

  • Dan Ariely Professor of psychology and behavioral economics, Duke University (Scholar)
    • Controlling the Information Flow: Effects on Consumers’ Decision Making and Preferences
      • One of the main objectives facing marketers is to present consumers with information on which to base their decisions. In doing so, marketers have to select the type of information system they want to utilize in order to deliver the most appropriate information to their consumers. One of the most interesting and distinguishing dimensions of such information systems is the level of control the consumer has over the information system. The current work presents and tests a general model for understanding the advantages and disadvantages of information control on consumers’ decision quality, memory, knowledge, and confidence. The results show that controlling the information flow can help consumers better match their preferences, have better memory and knowledge about the domain they are examining, and be more confident in their judgments. However, it is also shown that controlling the information flow creates demands on processing resources and therefore under some circumstances can have detrimental effects on consumers’ ability to utilize information. The article concludes with a summary of the findings, discussion of their application for electronic commerce, and suggestions for future research avenues.
      • This may be a good example of work that relates to socio-cultural interfaces.
  • Democracy’s Wisdom: An Aristotelian Middle Way for Collective Judgment
    • Josiah Ober (Scholar)
    •  The Greeks had experts determine choices, and the public vote between the expert choices
    • A satisfactory model of decision-making in an epistemic democracy must respect democratic values, while advancing citizens’ interests, by taking account of relevant knowledge about the world. Analysis of passages in Aristotle and legislative process in classical Athens points to a “middle way” between independent-guess aggregation and deliberation: an epistemic approach to decision-making that offers a satisfactory model of collective judgment that is both time-sensitive and capable of setting agendas endogenously. By aggregating expertise across multiple domains, Relevant Expertise Aggregation (REA) enables a body of minimally competent voters to make superior choices among multiple options, on matters of common interest. REA differs from a standard Condorcet jury in combining deliberation with voting based on judgments about the reputations and arguments of domain-experts.
  • NESTA Center for Collective Intelligence Design
    • The Centre for Collective Intelligence Design will explore how human and machine intelligence can be combined to make the most of our collective knowledge and develop innovative and effective solutions to social challenges.
    • Call for ideas (JuryRoom!)
      • Nesta is offering grants of up to £20,000 for projects that generate new knowledge on how to advance collective intelligence (combining human and machine intelligence) to solve social problems.
  • Synchronize gdrive, subversion
  • Finish abstract review
  • Organize iConf paper into something more coherent
    • Created folder for lit review
  • Start putting together notes on At Home in the Universe?
  • Ping folks from SASO
    • Graph Laplacian paper
    • Cycling stuff
  • Fika?
  • Meeting with Wayne?

Phil 9.8.18

How intermittent breaks in interaction improve collective intelligence

  • Many human endeavors—from teams and organizations to crowds and democracies—rely on solving problems collectively. Prior research has shown that when people interact and influence each other while solving complex problems, the average problem-solving performance of the group increases, but the best solution of the group actually decreases in quality. We find that when such influence is intermittent it improves the average while maintaining a high maximum performance. We also show that storing solutions for quick recall is similar to constant social influence. Instead of supporting more transparency, the results imply that technologies and organizations should be redesigned to intermittently isolate people from each other’s work for best collective performance in solving complex problems.

Will Foreign Agents Rig the U.S. Midterm Elections Through Social Media?

  • Samantha Bradshaw, an expert on computational propaganda, weighs in on whether Facebook, Twitter, and others are doing enough to curb political social media bots.

Detecting signs of dementia using word vector representations

  • Recent approaches to word vector representations, e.g., ‘w2vec’ and ‘GloVe’, have been shown to be powerful methods for capturing the semantics and syntax of words in a text. The approaches model the co-occurrences of words and recent successful applications on written text have shown how the vector representations and their interrelations represent the meaning or sentiment in the text. Most applications have targeted written language, however, in this paper, we investigate how these models port to the spoken language domain where the text is the result of (erroneous) automatic speech transcription. In particular, we are interested in the task of detecting signs of dementia in a person’s spoken language. This is motivated by the fact that early signs of dementia are known to affect a person’s ability to express meaning articulately for example when they engage in a conversation – something which is known to be cognitively very demanding. We analyse conversations designed to probe people’s short and long-term memory and propose three different methods for how word vectors may be used in a classification setup. We show that it is possible to identify dementia from the output of a speech recognizer despite a high occurrence of recognition errors.

Phil 8.31.18

7:00 – 5:00 ASRC MKT

  • The lightning round slides are in!
  • Get Speaker – done
  • Get posters – done
  • Haircut – done
  • drop off DME/KLR – done
  • Under Pressure response – done, I think?
  • upload ML excel files (done) to play around with graph laplacians some more – done
  • Print out two travel packets – done
  • create shared itinerary document – started. Aaron needs to finish his part
  • From KQED Silicon Valley Conversations The Future of Music: Computer or Composer
    • Ge Wang is an Associate Professor at Stanford University in the Center for Computer Research in Music and Acoustics (CCRMA). He specializes in the art of computer music design — researching programming languages and interactive software design for music, interaction design, expressive mobile music, new performance ensembles (laptop orchestra and mobile phone orchestra), human-computer interaction, visualization (sndpeek), music game design, aesthetics of technology-mediated design, and methodologies for education at the intersection of art, engineering, and design.
    • Doug Eck is a research scientist working on Magenta, a research project exploring the role of machine learning in the process of creating art and music. Primarily this involves developing new deep learning and reinforcement learning algorithms for generating songs, images, drawings, and other materials. But it’s also an exploration in building smart tools and interfaces that allow artists and musicians to extend (not replace!) their processes using these models. Started by me in 2016, Magenta now involves several researchers and engineers from the Google Brain team as well as many others collaborating via open source. Aside from Magenta, I’m working on sequence learning models for summarization and text generation as well new ways to improve AI-generated content based on user feedback.
    • Amy X Newburg has been developing her own brand of irreverently genre-crossing works for voice, live electronics and chamber ensembles for over 25 years, known for her innovative use of live looping technology with electronic percussion, her 4-octave vocal range and her colorful — often humorous — lyrics. One of the earliest performers to work with live digital looping, Amy has presented her solo “avant-cabaret” songs at such diverse venues as the Other Minds and Bang on a Can new music festivals, the Berlin International Poetry Festival, the Wellington and Christchurch Jazz Festivals (New Zealand), the Warsaw Philharmonic Hall, electronic music festivals, colleges, rock clubs and concert halls throughout the U.S. and abroad.
  • Teens, Social Media & Technology 2018
    • YouTube, Instagram and Snapchat are the most popular online platforms among teens. Fully 95% of teens have access to a smartphone, and 45% say they are online ‘almost constantly’
  • Aaron found this: Density-functional fluctuation theory of crowds
    • A primary goal of collective population behavior studies is to determine the rules governing crowd distributions in order to predict future behaviors in new environments. Current top-down modeling approaches describe, instead of predict, specific emergent behaviors, whereas bottom-up approaches must postulate, instead of directly determine, rules for individual behaviors. Here, we employ classical density functional theory (DFT) to quantify, directly from observations of local crowd density, the rules that predict mass behaviors under new circumstances. To demonstrate our theory-based, data-driven approach, we use a model crowd consisting of walking fruit flies and extract two functions that separately describe spatial and social preferences. The resulting theory accurately predicts experimental fly distributions in new environments and provides quantification of the crowd “mood”. Should this approach generalize beyond milling crowds, it may find powerful applications in fields ranging from spatial ecology and active matter to demography and economics.
    • Here’s an interesting part: The DFFT analysis that we present is particularly powerful because it separates the influence of the environment on agents from interactions among those agents. 
      • This implies that it should (could? might?) be possible to calculate a social/environmental ratio for individual agents. High environmental are nomadic. High social are stampede-prone. Need to dig in further.
  • Mechanical Vibrations and Waves » Lecture 4: Coupled Oscillators, Normal Modes
    Lecture 4: Coupled Oscillators, Normal Modes (MIT opencourseware)

    • Prof. Lee analyzes a highly symmetric system which contains multiple objects. By physics intuition, one could identify a special kind of motion – the normal modes. He shows that there is a general strategy for solving the normal modes.
      • Every part of the system is oscillating at the same frequency and the same phase
      • Stopped at 42:07 to take a break. I think this is the right track though. Download this for the plane?
  • Chapter on normal modes

Phil 8.30.18

7:00 – 5:00  ASRC MKT

  • Target Blue Sky paper for iSchool/iConference 2019: The chairs are particularly looking for “Blue Sky Ideas” that are open-ended, possibly even “outrageous” or “wacky,” and present new problems, new application domains, or new methodologies that are likely to stimulate significant new research. 
  • I’m thinking that a paper that works through the ramifications of this diagram as it relates to people and machines. With humans that are slow responding with spongy, switched networks the flocking area is large. With a monolithic densely connected system it’s going to be a straight line from nomadic to stampede. Nomad-Flocking-Stampede2
    • Length: Up to 4 pages (excluding references)
    • Submission deadline: October 1, 2018
    • Notification date: mid-November, 2018
    • Final versions due: December 14, 2018
    • First versions will be submitted using .pdf. Final versions must be submitted in .doc, .docx or La Tex.
  • More good stuff on BBC Business Daily Trolling for Cash
    • Anger and animosity is prevalent online, with some people even seeking it out. It’s present on social media of course as well as many online forums. But now outrage has spread to mainstream media outlets and even the advertising industry. So why is it so lucrative? Bonny Brooks, a writer and researcher at Newcastle University explains who is making money from outrage. Neuroscientist Dr Dean Burnett describes what happens to our brains when we see a comment designed to provoke us. And Curtis Silver, a tech writer for KnowTechie and ForbesTech, gives his thoughts on what we need to do to defend ourselves from this onslaught of outrage.
  • Exposure to Opposing Views can Increase Political Polarization: Evidence from a Large-Scale Field Experiment on Social Media
    • Christopher Bail (Scholar)
    • There is mounting concern that social media sites contribute to political polarization by creating “echo chambers” that insulate people from opposing views about current events. We surveyed a large sample of Democrats and Republicans who visit Twitter at least three times each week about a range of social policy issues. One week later, we randomly assigned respondents to a treatment condition in which they were offered financial incentives to follow a Twitter bot for one month that exposed them to messages produced by elected officials, organizations, and other opinion leaders with opposing political ideologies. Respondents were re-surveyed at the end of the month to measure the effect of this treatment, and at regular intervals throughout the study period to monitor treatment compliance. We find that Republicans who followed a liberal Twitter bot became substantially more conservative post-treatment, and Democrats who followed a conservative Twitter bot became slightly more liberal post-treatment. These findings have important implications for the interdisciplinary literature on political polarization as well as the emerging field of computational social science.
  • Setup gcloud tools on laptop – done
  • Setup Tensorflow on laptop. Gave up un using CUDA 9.1, but got tf doing ‘hello, tensorflow’
  • Marcom meeting – 2:00
  • Get the concept of behaviors being a more scalable, dependable way of vetting information.
    • Eg Watching the DISI of outrage as manifested in trolling
      • “Uh. . . . not to be nitpicky,,,,,but…the past tense of drag is dragged, not drug.”: An overview of trolling strategies
        • Dr Claire Hardaker (Scholar) (Blog)
          • I primarily research aggression, deception, and manipulation in computer-mediated communication (CMC), including phenomena such as flaming, trolling, cyberbullying, and online grooming. I tend to take a forensic linguistic approach, based on a corpus linguistic methodology, but due to the multidisciplinary nature of my research, I also inevitably branch out into areas such as psychology, law, and computer science.
        • This paper investigates the phenomenon known as trolling — the behaviour of being deliberately antagonistic or offensive via computer-mediated communication (CMC), typically for amusement’s sake. Having previously started to answer the question, what is trolling? (Hardaker 2010), this paper seeks to answer the next question, how is trolling carried out? To do this, I use software to extract 3,727 examples of user discussions and accusations of trolling from an eighty-six million word Usenet corpus. Initial findings suggest that trolling is perceived to broadly fall across a cline with covert strategies and overt strategies at each pole. I create a working taxonomy of perceived strategies that occur at different points along this cline, and conclude by refining my trolling definition.
        • Citing papers
  • FireAnt (Filter, Identify, Report, and Export Analysis Toolkit) is a freeware social media and data analysis toolkit with built-in visualization tools including time-series, geo-position (map), and network (graph) plotting.
  • Fix marquee – done
  • Export to ppt – done!
    • include videos – done
    • Center title in ppt:
      • model considerations – done
      • diversity injection – done
  • Got the laptop running Python and Tensorflow. Had a stupid problem where I accidentally made a virtual environment and keras wouldn’t work. Removed, re-connected and restarted IntelliJ and everything is working!

Phil 8.29.18

7:00 – 4:30 ASRC MKT

  • Editing videos
  • Need to think about short CHI paper about designing for culture/robot interactions. The trolly problem at scale? How would the sim be set up? The amount of randomness at the initial condition? Stiffness vs. connectivity? Beleif space is still important and is actually used as a concept in path planning
  • Visual Exploration and Comparison of Word Embeddings
    • Word embeddings are distributed representations for natural language words, and have been wildly used in many natural language processing tasks. The word embedding space contains local clusters with semantically similar words and meaningful directions, such as the analogy. However, there are different training algorithms and text corpora, which both have a different impact on the generated word embeddings. In this paper, we propose a visual analytics system to visually explore and compare word embeddings trained by different algorithms and corpora. The word embedding spaces are compared from three aspects, i.e., local clusters, semantic directions and diachronic changes, to understand the similarity and differences between word embeddings.
  • Much work on slides
  • Can’t get Google to recognise my account?
    curl.exe -H "Content-Type: application/json" -H "Authorization: Bearer "$(gcloud auth application-default print-access-token) https://speech.google
    apis.com/v1/speech:recognize -d @sync-request.json
    curl: (6) Could not resolve host: ya29.c.EloHBu32-0nBAqimi1Zumlot6rjGtGpUk27qTTESRLW4vtd1LY4ihxBIesU3ga-kmwCaM7YZS-JRo_KNjaC_bj13dWazBcKr4YtAEQYFzSpSBx3DwdS46DTt0bg
    {
      "error": {
        "code": 403,
        "message": "The request is missing a valid API key.",
        "status": "PERMISSION_DENIED"
      }
    }

    No idea what host: ya29.c.EloHBu32-0nBAqimi1Zumlot6rjGtGpUk27qTTESRLW4vtd1LY4ihxBIesU3ga-kmwCaM7YZS-JRo_KNjaC_bj13dWazBcKr4YtAEQYFzSpSBx3DwdS46DTt0bg is

  • Found a problem with the poster. There are two herding DTW charts. Must be reprinted

Phil 8.27.18

7:00 – 5:00 ASRC MKT

  • Good chat with Barbara yesterday. She suggests horse racing podcasts, since the question is always the same “who’s going to win today” and the information to discuss is much more constrained. Additionally, there is the wagering information that could be used to determine the level of consensus?
  • Found an idiom translator! “Swing of the pendulum” occurs at least in French, German and Italian
  • Downloaded the new videos Need to put them in the ppt when the slides stabilize
  • Pinged Wayne about getting together today
  • Changed the questions page to have English, Italian, French and German terms for belief space
  • Another example of diversity injection (twitter)
  • Working on podcast text handling
      • Created the MapsFromPodcasts project in Development
      • Created an new key and downloaded the key json file
      • Installed Google Cloud Tools (213.0.0), following the directions of this page. Wow. Lots of stuff!
        Output folder: D:\Programs\GoogleCloudAPI
        Downloading Google Cloud SDK core.
        Extracting Google Cloud SDK core.
        Create Google Cloud SDK bat file: D:\Programs\GoogleCloudAPI\cloud_env.bat
        Installing components.
        Welcome to the Google Cloud SDK!
        Your current Cloud SDK version is: 213.0.0
        Installing components from version: 213.0.0
        +-----------------------------------------------------------------------------+
        | These components will be installed. |
        +-----------------------------------------------------+------------+----------+
        | Name | Version | Size |
        +-----------------------------------------------------+------------+----------+
        | BigQuery Command Line Tool | 2.0.34 | < 1 MiB |
        | BigQuery Command Line Tool (Platform Specific) | 2.0.34 | < 1 MiB |
        | Cloud SDK Core Libraries (Platform Specific) | 2018.06.18 | < 1 MiB |
        | Cloud Storage Command Line Tool | 4.33 | 3.6 MiB |
        | Cloud Storage Command Line Tool (Platform Specific) | 4.32 | < 1 MiB |
        | Cloud Tools for PowerShell | | |
        | Cloud Tools for PowerShell | 1.0.1.8 | 17.9 MiB |
        | Default set of gcloud commands | | |
        | Windows command line ssh tools | | |
        | Windows command line ssh tools | 2017.09.15 | 1.8 MiB |
        | gcloud cli dependencies | 2018.08.03 | 1.3 MiB |
        +-----------------------------------------------------+------------+----------+
        For the latest full release notes, please visit:
        https://cloud.google.com/sdk/release_notes
        #============================================================#
        #= Creating update staging area =#
        #============================================================#
        #= Installing: BigQuery Command Line Tool =#
        #============================================================#
        #= Installing: BigQuery Command Line Tool (Platform Spec... =#
        #============================================================#
        #= Installing: Cloud SDK Core Libraries (Platform Specific) =#
        #============================================================#
        #= Installing: Cloud Storage Command Line Tool =#
        #============================================================#
        #= Installing: Cloud Storage Command Line Tool (Platform... =#
        #============================================================#
        #= Installing: Cloud Tools for PowerShell =#
        #============================================================#
        #= Installing: Cloud Tools for PowerShell =#
        #============================================================#
        #= Installing: Default set of gcloud commands =#
        #============================================================#
        #= Installing: Windows command line ssh tools =#
        #============================================================#
        #= Installing: Windows command line ssh tools =#
        #============================================================#
        #= Installing: gcloud cli dependencies =#
        #============================================================#
        #= Creating backup and activating new installation =#
        #============================================================#
        Performing post processing steps...
        ..............................................................................................................................................................done.
        Update done!
        This will install all the core command line tools necessary for working with
        the Google Cloud Platform.
        For more information on how to get started, please visit:
        https://cloud.google.com/sdk/docs/quickstarts
        Google Cloud SDK has been installed!

         

     

    • Google is sooooooooooooooooooooo Unix/Linux
  • Meeting with Wayne
    • Fix slides some more
    • Email about demo and poster – done

Phil 8.26.18

Listening to On Being with guest Mahzarin Banaji (Scholar)

  • The other thing that I do is to actually create inputs into my mind of my own making. I do think that in some ways our brains are simple and that they will believe that things are real even if they’re not. So, that’s what movies do. That’s what novels do for us. So what if I have a series of 1,000 pictures that rotate through on my screen saver of people who come from many parts of the world that I will never, ever see or even think about. Look, just take an example close by. I have no idea what life for a farmer in Iowa is. I bet it’s hard. I bet I have no idea what they have to deal with. I don’t think I will ever truly understand.But, right now, they are a distant group in my mind. I live in Cambridge, Massachusetts, and I don’t think about farming and farmers. If my screensaver literally just points out the existence of such people and what their issues might be, I believe that my brain is going to begin to care at some level. And if I show myself possibilities that don’t exist easily, that’s even better.
  • A nice example of diversity injection

Phil 8.23.18

7:00 – 5:30 ASRC MKT

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  • Slides
    • Groups/tribes stay the same, but the topics change
    • Past polarizing topics:
      • Confederate statues
      • Kneeling for the national anthem
      • #blacklivesmatter
      • Hoodies
      • Crack cocaine
      • 1968 Olympics Black Power salute
      • Alabama bus boycott
    • Stiffening a group creates a stampede (In-group high SIH)
    • Adding group-invisible diversity disrupts the velocity and direction of a stampede
    • Arendt/Moscovici slide “So we’re doomed, right! Except…”
    • See what velocity of the disrupted stampede looks like
  • Why Trump Supporters Believe He Is Not Corrupt
    • The answer may lie in how Trump and his supporters define corruption. In a forthcoming book titled How Fascism Works, the Yale philosophy professor Jason Stanley makes an intriguing claim. “Corruption, to the fascist politician,” he suggests, “is really about the corruption of purity rather than of the law. Officially, the fascist politician’s denunciations of corruption sound like a denunciation of political corruption. But such talk is intended to evoke corruption in the sense of the usurpation of the traditional order.”
  • Climate science proposals are being reviewed by Ryan Zinke’s old football buddy. Seriously.
    • But what if the corruption isn’t hidden at all, but right out in the open? What if, when it’s identified, the perpetrator doesn’t apologize, or demonstrate any remorse or shame, and there’s no punishment? What then? We don’t really have good narratives around what happens in that situation, which is why the Trump administration so often leaves us sputtering and gawking. It can’t just be a motley collection of incompetent grifters, each misruling their own little fiefdom, trying to stay in their boss’s good graces, succeeding less through wits than a congenital lack of shame and the unstinting institutional support of GOP donors. Can it?

Phil 8.22.18

7:00 – 4:00 ASRC MKT

Phil 8.21.18

7:00 – 3:00 ASRC MKT

  • Rework the slides
    • Explicit introduction, lit review, methods, results, conclusion and discussion slides
    • Slide for the difference between opinion dynamics & consensus formation as a static end  and part of a dynamic process. (Tribe membership may be static, belief of the tribe is highly dynamic. It’s the story for the group)
    • Revisit stampede/flock/nomad slide in the conclusions
    • Lose the following slides:
      • Belief space
      • Theory slide replace with a slide that breaks out the to knobs of dimension reduction and social influence horizons. The slide is called “the simple trick” Explain how herding affects these knobs by presenting simple issues and making the network stiffer through weight and connection
    • Get rid of optical polarization
  • Fanning the Flames of Hate: Social Media and Hate Crime
    • This paper investigates the link between social media and hate crime using Facebook data. We study the case of Germany, where the recently emerged right-wing party Alternative für Deutschland (AfD) has developed a major social media presence. We show that right-wing anti-refugee sentiment on Facebook predicts violent crimes against refugees in otherwise similar municipalities with higher social media usage. To further establish causality, we exploit exogenous variation in major internet and Facebook outages, which fully undo the correlation between social media and hate crime. We further find that the effect decreases with distracting news events; increases with user network interactions; and does not hold for posts unrelated to refugees. Our results suggest that social media can act as a propagation mechanism between online hate speech and real-life violent crime.
  • Facebook is rating the trustworthiness of its users on a scale from zero to 1
    • Facebook has begun to assign its users a reputation score, predicting their trustworthiness on a scale from zero to 1.
    • Tessa Lyons, product manager who is in charge of fighting misinformation (video)
  • Social Science One
    • implements a new type of partnership between academic researchers and private industry to advance the goals of social science in understanding and solving society’s greatest challenges. The partnership enables academics to analyze the increasingly rich troves of information amassed by private industry in responsible and socially beneficial ways. It ensures the public maintains privacy while gaining societal value from scholarly research. And it enables firms to enlist the scientific community to help them produce social good, while protecting their competitive positions.
  • Lost Causes Is this fashion in economic theory (found via Twitter)?Causal
  • Poster printing – UMBC Commonvision

Phil 8.19.18

7:00 – 5:30 ASRC MKT

  • Had a thought that the incomprehension that comes from misalignment that Stephens shows resembles polarizing light. I need to add a slider that enables influence as a function of alignment. Done
    • Getting the direction cosine between the source and target belief
      double interAgentDotProduct = unitOrientVector.dotProduct(otherUnitOrientVector);
      double cosTheta = Math.min(1.0, interAgentDotProduct);
      double beliefAlignment = Math.toDegrees(Math.acos(cosTheta));
      double interAgentAlignment = (1.0 - beliefAlignment/180.0);
    • Adding a global variable that sets how much influence (0% – 100%) influence from an opposing agent. Just setting it to on/off, because the effects are actually pretty subtle
  • Add David’s contributions to slide one writeup – done
  • Start slide 2 writeup
  • Find casters for Dad’s walker
  • Submit forms for DME repair
    • Drat – I need the ECU number
  • Practice talk!
    • Need to reduce complexity and add clearly labeled sections, in particular methods
  • I need to start paying attention to attention
  • Also, keeping this on the list How social media took us from Tahrir Square to Donald Trump by Zeynep Tufekci
  • Social Identity Threat Motivates Science – Discrediting Online Comments
    • Experiencing social identity threat from scientific findings can lead people to cognitively devalue the respective findings. Three studies examined whether potentially threatening scientific findings motivate group members to take action against the respective findings by publicly discrediting them on the Web. Results show that strongly (vs. weakly) identified group members (i.e., people who identified as “gamers”) were particularly likely to discredit social identity threatening findings publicly (i.e., studies that found an effect of playing violent video games on aggression). A content analytical evaluation of online comments revealed that social identification specifically predicted critiques of the methodology employed in potentially threatening, but not in non-threatening research (Study 2). Furthermore, when participants were collectively (vs. self-) affirmed, identification did no longer predict discrediting posting behavior (Study 3). These findings contribute to the understanding of the formation of online collective action and add to the burgeoning literature on the question why certain scientific findings sometimes face a broad public opposition.

Phil 8.18.18

This looks good:

  • Created almost 25 years ago, when the web was in its infancy, Propaganda Critic is dedicated to promoting techniques of propaganda analysis among critically minded citizens.

    In 2018, realizing that traditional approaches to propaganda analysis were not well-suited for making sense out of our contemporary political crisis, we completely overhauled Propaganda Critic to take into account the rise of ‘computational propaganda.’ In addition to updating all of the original content, we added nearly two dozen new articles exploring the rise of computational propaganda, explaining recent research on cognitive biases that influence how we interpret and retain information, and presenting recent case studies of how propaganda techniques have been used to disrupt democracy around the world.

Continuing to work on the SASO writeup – it’s coming along. Slower than I’d like…

This is just too good:

  • Data Organization in Spreadsheets
    • Spreadsheets are widely used software tools for data entry, storage, analysis, and visualization. Focusing on the data entry and storage aspects, this article offers practical recommendations for organizing spreadsheet data to reduce errors and ease later analyses. The basic principles are: be consistent, write dates like YYYY-MM-DD, do not leave any cells empty, put just one thing in a cell, organize the data as a single rectangle (with subjects as rows and variables as columns, and with a single header row), create a data dictionary, do not include calculations in the raw data files, do not use font color or highlighting as data, choose good names for things, make backups, use data validation to avoid data entry errors, and save the data in plain text files.

Phil 8.17.18

7:00 – 4:30 ASRC MKT

Phil 8.16.18

7:00 – 4:30 ASRC MKT

  • R2D3 is an experiment in expressing statistical thinking with interactive design. Find us at @r2d3usR2D3
  • Foundations of Temporal Text Networks
    • Davide Vega (Scholar)
    • Matteo Magnani (Scholar)
    • Three fundamental elements to understand human information networks are the individuals (actors) in the network, the information they exchange, that is often observable online as text content (emails, social media posts, etc.), and the time when these exchanges happen. An extremely large amount of research has addressed some of these aspects either in isolation or as combinations of two of them. There are also more and more works studying systems where all three elements are present, but typically using ad hoc models and algorithms that cannot be easily transferred to other contexts. To address this heterogeneity, in this article we present a simple, expressive and extensible model for temporal text networks, that we claim can be used as a common ground across different types of networks and analysis tasks, and we show how simple procedures to produce views of the model allow the direct application of analysis methods already developed in other domains, from traditional data mining to multilayer network mining.
      • Ok, I’ve been reading the paper and if I understand it correctly, it’s pretty straightforward and also clever. It relates a lot to the way that I do term document matrices, and then extends the concept to include time, agents, and implicitly anything you want to. To illustrate, here’s a picture of a tensor-as-matrix: tensorIn2DThe important thing to notice is that there are multiple dimensions represented in a square matrix. We have:
        • agents
        • documents
        • terms
        • steps
      • This picture in particular is of an undirected adjacency matrix, but I think there are ways to handle in-degree and out-degree, though I think that’s probably better handled by having one matrix for indegree and one for out.
      • Because it’s a square matrix, we can calculate the steps between any node that’s on the matrix, and the centrality, simply by squaring the matrix and keeping track of the steps until the eigenvector settles. We can also weight nodes by multiplying that node’s row and column by the scalar. That changes the centrality, but ot the connectivity. We can also drop out components (steps for example) to see how that changes the underlying network properties.
      • If we want to see how time affects the development of the network, we can start with all the step nodes set to a zero weight, then add them in sequentially. This means, for example, that clustering could be performed on the nonzero nodes.
      • Some or all of the elements could be factorized using NMF, resulting in smaller, faster matrices.
      • Network embedding could be useful too. We get distances between nodes. And this looks really important: Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec
      • I think I can use any and all of the above methods on the network tensor I’m describing. This is very close to a mapping solution.
  • The Shifting Discourse of the European Central Bank: Exploring Structural Space in Semantic Networks (cited by the above paper)
    • Convenient access to vast and untapped collections of documents generated by organizations is a valuable resource for research. These documents (e.g., Press releases, reports, speech transcriptions, etc.) are a window into organizational strategies, communication patterns, and organizational behavior. However, the analysis of such large document corpora does not come without challenges. Two of these challenges are 1) the need for appropriate automated methods for text mining and analysis and 2) the redundant and predictable nature of the formalized discourse contained in these collections of texts. Our article proposes an approach that performs well in overcoming these particular challenges for the analysis of documents related to the recent financial crisis. Using semantic network analysis and a combination of structural measures, we provide an approach that proves valuable for a more comprehensive analysis of large and complex semantic networks of formal discourse, such as the one of the European Central Bank (ECB). We find that identifying structural roles in the semantic network using centrality measures jointly reveals important discursive shifts in the goals of the ECB which would not be discovered under traditional text analysis approaches.
  • Comparative Document Analysis for Large Text Corpora
    • This paper presents a novel research problem, Comparative Document Analysis (CDA), that is, joint discovery of commonalities and differences between two individual documents (or two sets of documents) in a large text corpus. Given any pair of documents from a (background) document collection, CDA aims to automatically identify sets of quality phrases to summarize the commonalities of both documents and highlight the distinctions of each with respect to the other informatively and concisely. Our solution uses a general graph-based framework to derive novel measures on phrase semantic commonality and pairwise distinction, where the background corpus is used for computing phrase-document semantic relevance. We use the measures to guide the selection of sets of phrases by solving two joint optimization problems. A scalable iterative algorithm is developed to integrate the maximization of phrase commonality or distinction measure with the learning of phrase-document semantic relevance. Experiments on large text corpora from two different domains—scientific papers and news—demonstrate the effectiveness and robustness of the proposed framework on comparing documents. Analysis on a 10GB+ text corpus demonstrates the scalability of our method, whose computation time grows linearly as the corpus size increases. Our case study on comparing news articles published at different dates shows the power of the proposed method on comparing sets of documents.
  • Social and semantic coevolution in knowledge networks
    • Socio-semantic networks involve agents creating and processing information: communities of scientists, software developers, wiki contributors and webloggers are, among others, examples of such knowledge networks. We aim at demonstrating that the dynamics of these communities can be adequately described as the coevolution of a social and a socio-semantic network. More precisely, we will first introduce a theoretical framework based on a social network and a socio-semantic network, i.e. an epistemic network featuring agents, concepts and links between agents and between agents and concepts. Adopting a relevant empirical protocol, we will then describe the joint dynamics of social and socio-semantic structures, at both macroscopic and microscopic scales, emphasizing the remarkable stability of these macroscopic properties in spite of a vivid local, agent-based network dynamics.
  • Tensorflow 2.0 feedback request
    • Shortly, we will hold a series of public design reviews covering the planned changes. This process will clarify the features that will be part of TensorFlow 2.0, and allow the community to propose changes and voice concerns. Please join developers@tensorflow.org if you would like to see announcements of reviews and updates on process. We hope to gather user feedback on the planned changes once we release a preview version later this year.

Phil 8.13.18

7:00 – 4:30 ASRC MKT