7:00 – 3:00 ASRC MKT

• Organized my thoughts on trust and awareness
• GMap: Drawing Graphs as Maps (also Visualizing Graphs and Clusters as Maps)
  • Yifan Hu – I am a member of the Yahoo Research (New York) working on data mining, machine learning and visualization. Before joining Yahoo I was a member of the Information Visualization department at AT&T Labs — Research, working on graph and text visualization, machine learning and numerical algorithms. From 2001 to 2007, I worked at Wolfram Research, developing numerical and graph theoritical software. Prior to April 2001, I worked in the Computational Science and Engineering Department at Daresbury Laboratory, conducting research in algorithms for high performance computing. For further chronological details, see here.
  • Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through dimensionality reduction techniques. However, these traditional methods often do not capture well the underlying structural information, clustering, and neighborhoods. In this paper, we describe GMap: a practical tool for visualizing relational data with geographic-like maps. We illustrate the effectiveness of this approach with examples from several domains All the maps referenced in this paper can be found in this http URL
• Need to take a look at these and see if there is disagreement on the location of physical objects, or it is the layering of conceptual objects such as borders on the map.
  • Why Amazonian forest peoples are ‘counter-mapping’ their ancestral lands
  • Whose woods are these? counter-mapping forest territories in Kalimantan, Indonesia
  • Cartography, territory, property: postcolonial reflections on indigenous counter-mapping in Nicaragua and Belize
• Finished the first pass at the CHI DC proposal!
• ACM has built an ENTIRELY new LaTex format for extended CHI abstracts that breaks when you look at it sideways (https://github.com/sigchi/Document-Formats). I have literally spent the last two-three hours trying to:
  1. make a single author (success!)
  2. get the abstract in (partial success?)
  3. get the figures to work
  4. bring in any other text
  5. get the bibliography to work. (At all. I mean, like adding a single citation breaks everything.)

Phil 7:00 – 5:00 ASRC MKT

• Register for MLconf
• Scrum!
• Write up GLOBE concept
• Does Twitter now set the news agenda? – Very valuable for mapping
  •  Indexing theory, in brief, states that the content of media reports reflects the degree to which elites – politicians and leaders in government in particular – are in agreement or disagreement. The greater the level of agreement or consensus among elites, the less news there is to report in terms of elite conflict. This is not to say that a consensus among elites is not newsworthy; indexing theory conveys how media reporting is a function of the multiple voices that exist when there is elite debate
  • From this paper: Politicians and the Policy Agenda: Does Use of Twitter by the U.S. Congress Direct New York Times Content?
• This is kind of what I was going to do when I started on my PhD studies. Funny how things change. Did get a poster out of it though.
• Sent Aaron a note that maybe there should be an ASRCresearch domain (.org?) or ASRCFederal.com/research. He’ll start floating that.
• Since I think that Trust is a social construct for groups to deal with complete information and that Awareness is a measure of the completeness of the information, I started to search for collective game theory trust. The main term that comes up is collective action.
• There is also a thing called decision space:
  • A Class of Solutions for Group Decision Problems Given a set of utility functions defined on a decision apace for a group of individuals, we introduce the concept of utopia point for the group o.a well o.a the group regret of a feasible decision. The group regret of a decision varies with a class of distance functions. The class of solutions under study are those which minimize the group regret according to the closs of distance functions. We investigate its properties from the viewpoint of decision rationale. The bounds and monotonicity of the solutions together with their computation are also explored
  • Multiple-criteria decision analysis
• Some interesting DC extended abstracts:
  • Using Data Visualisation to tell Stories about Cultural Collections
  • Computational Design of Input Methods
  • News Company’s Link Sharing on Twitter as Informative Advertising and Content Signaling
  • Behind The Wikipedia Medical Knowledge Factory: Understanding the Knowledge Dynamic Over Time
• Finished the alignment calculations and charting. Here’s an example: 
• Meeting with Cindy
  • We spent some time looking at mind maps and discussing documentation. The main point is that the documentation trail should be clear – engineer’s notebook, wordpress blog, etc.
  • She’s going to look into finding the NASA scenarios that Wayne spoke of
  • We realized that escape rooms are a possibly a group polarization game
  • Gave her three papers to look at
    • Group and computer-mediated discussion effects in risk decision making
    • Group Polarization and Computer-Mediated Communication
    • One more that I found that was on leadership stress games
  • Need to get her this one too:
    • The effects of a normative intervention on group decision-making performance

8:00 – 5:00 ASRC MKT

• The CHIIR paper is submitted! Incorporated all of Wayne’s points (that I could decipher)
• Change the angle recording code so that it is WRT the average heading of the population. Might make a better figure 7. Started.
• Security training – one hour – done
• Do Charlestown things – done
• Fika
  • Anita skimmed the paper and liked what she saw.
  • NVivo webinar
  • $120/year
• Meeting with Wayne?
  • The CHI deadline is next week: https://chi2018.acm.org/authors/doctoral-consortium/
  • Extended Abstracts from CHI 17 (search for SESSION: Doctoral Consortium)
  • Some extended discussion about GLOBE. Might have the opportunity to look at the code with some guidance. Otherwise, it’s going up on GitHub soon. I’d like to see the code that finds similar remotely observed data on the globe as a way to find similar papers. In this scenario, that could be used to equate new GEOS data (soil, vegetation, lighting, etc) to use places that are burning to places that are at high risk for burning.

7:00 – 5:00 ASRC MKT

• Sent out copies of the draft to academic/work management. Waiting for comments
• Fix concepts
• Fix Keywords – going to try the LMN on the lit review and see what pops up 
  • Raw: platform model market dependence network effect simulation smartphone technology (Scholar search on these terms)
  • Normalized: group information model study between social system individual change (Scholar search on these terms)
  • Normalized is much better.
• Get page numbers
• Register for easychair, and make sure what the actual deadline is. Registered, but there is no date information WRT the submission. Going to submit Saturday night out of an abundance of caution.
• I had some more thoughts about how behavior patterns emerge from the interplay between trust and awareness. I think the following may be true:
  • Healthy behaviors emerge when trust and awareness are equivalent.
  • Low trust and low awareness is reasonable. It’s like walking through a dark, unknown space. You go slow, bump into things, and adjust.
  • Low trust and high awareness is paralytic.
  • High trust and low awareness is reckless. Runaway conditions like echo chambers.
  • Diversity is a mechanism for extending awareness, but it depends on trusting those who are different. That may be the essence of the explore/exploit dilemma.
  • In a healthy group context, trust falls off as a function of awareness. That’s why we get flocking. That is the pattern that emerges when you trust more those who are close, while they in turn do the same, building a web of interaction. It’s kind of like interacting ripples?
  • This may work for any collection of entities that have varied states that undergo change in some predictable way. If they were completely random, then awareness of the state is impossible, and trust should be zero.
    1. Human agent trust chains might proceed from self to family to friends to community, etc.
    2. Machine agent trust chains might proceed from self to direct connections (thumb drives, etc) to LAN/WAN to WAN
    3. Genetic agent trust chain is short – self to species. Contact is only for reproduction. Interaction would reflect the very long sampling times.
    4. Note that (1) is evolved and is based on incremental and repeated interactions, while (2) is designed and is based on arbitrary rules that can change rapidly. Genetics are maybe dealing with different incentives? The only issue is persisting and spreading (which helps in the persisting)
  • Computer-mediated-communication disturbs this process (as does probably every form of mass communication) because the trust in the system is applied to the trust of the content. This can work in both ways. For example, lowering trust in the press allows for claims of Fake News. Raising the trust of social networks that channel anonymous online sources allows for conspiracy thinking.
  • An emerging risk is how this affects artificial intelligence, given that currently high trust in the algorithms and training sets is assumed by the builders
    • Low numbers of training sets mean low diversity/awareness,
    • Low numbers of algorithms (DNNs) also mean low diversity/awareness
    • Since training/learning is spread by update, the installed base is essentially multiple instances of the same individual. So no diversity and very high trust. That’s a recipe for a stampede of 10,000 self driving cars.

7:00 – 4:00 ASRC MKT

• from ABC news. Artificially amplifying (both) poles and establishing norms
  • “They were taking both sides of the argument this past weekend, and pushing them out from their troll farms as much as they could to try to just raise the noise level in America and to make a big issue seem like an even bigger issue,” Lankford said at a hearing of the Senate Homeland Security and Government Affairs Committee.
• Got all the LaTex packages installed so that I can compile the paper at home
• Adding in references – done
• Fix concepts
• Fix Keywords

8:00 – 4:30 ASRC MKT

• Building an information stampede in Iowa
• Rework scale sentence
• Change ‘Runaway Echo Chambers’ to ‘Runaway Belief Bubbles’? No. Echo Chambers without the Runway, we’re thinking…
• Done stuffing the paper into LaTex! Ten pages!

9:00 – 5:00 ASRC MKT

• Cleaning up text
• Generating figures
• 4:00 Meeting with Wayne
  • Wayne feedback on last two sections (now-ish)
  • Anita reciprocal read for papers Wed/Thu/Fri?
  • Wayne edit Fri/Sat/Sun

7:00 – 7:00 ASRC MKT

• This is pretty cool: 
  • The charts and graphs here display hashtags, topics and URLs promoted by Russia-linked influence networks on Twitter. Content is not necessarily produced or created by Russian government operatives, although that is sometimes the case. Instead, the network often opportunistically amplifies content created by third parties not directly linked to Russia. Common themes for amplification include content attacking the U.S. and Europe, conspiracy theories and disinformation. Russian influence operations also frequently promote extremism and divisive politics in Western countries. Just because the Russia-aligned network monitored here tweets something, that doesn’t mean everyone who tweets the same content is aligned with Russia. For a detailed discussion of this dashboard’s methodology, click here.
• Linking Resilience Thinking and Transformative Change: Taking Development
  • The United Nations Research Institute for Social Development (UNRISD) is an autonomous research institute within the UN system that undertakes multidisciplinary research and policy analysis on the social dimensions of contemporary development issues.
• Mark Zuckerberg Can’t Stop You From Reading This Because The Algorithms Have Already Won
• Final week before the paper is due!!
• Peng’s defense at 10:00
  • Cross-language Information Retrieval
  • Multilingual …
  • Non Native English Searchers NNES
  • Two types of IR research. Looking at people behave outside the computer, and looking at traces of the behavior inside the computer
  • Consolidated query reformulation definition table. Nice. Need to get that (from Wayne?)
• Bots are powerful means of normalizing extremism: “create false sense of consensus, intimidate people who speak out”
  • A Step-By-Step Guide For How Russian Bots Trick Far-Right Trolls Into Spreading Fake News
• Spatial-Semantics – How Users Derive Shape from Information Space
  • Downloaded – Printed out a copy for Cindy to read.
• The UTOPIAN paper does not show up when you look for it on scholar. Had to get it by going through Jaegul Choo’s link. And it’s his most-cited paper! Gatekeepers…
• First draft is done, if I don’t do the future work.

Aaaaand it’s fall. Darkness looms…

7:00 – 10:30, 12:30 – 6:00 ASRC MKT

• Working on discussion and implications for design sections. Should there be a Future Work? Could discuss the network analysis, CellAccumulator and game/mapping work
• Resilience: The emergence of a perspective for social–ecological systems analyses Downloaded. This looks like a must-read.
  • Carl Folke – science director and co-founder of the Stockholm Resilience Centre (SRC). He has extensive experience in transdisciplinary collaboration between natural and social scientists and is among the most cited scientists in the world on resilience thinking
  • The resilience perspective is increasingly used as an approach for understanding the dynamics of social–ecological systems. This article presents the origin of the resilience perspective and provides an overview of its development to date. With roots in one branch of ecology and the discovery of multiple basins of attraction in ecosystems in the 1960–1970s, it inspired social and environmental scientists to challenge the dominant stable equilibrium view. The resilience approach emphasizes non-linear dynamics, thresholds, uncertainty and surprise, how periods of gradual change interplay with periods of rapid change and how such dynamics interact across temporal and spatial scales. The history was dominated by empirical observations of ecosystem dynamics interpreted in mathematical models, developing into the adaptive management approach for responding to ecosystem change. Serious attempts to integrate the social dimension is currently taking place in resilience work reflected in the large numbers of sciences involved in explorative studies and new discoveries of linked social–ecological systems. Recent advances include understanding of social processes like, social learning and social memory, mental models and knowledge–system integration, visioning and scenario building, leadership, agents and actor groups, social networks, institutional and organizational inertia and change, adaptive capacity, transformability and systems of adaptive governance that allow for management of essential ecosystem services.

7:00 – 4:00 ASRC MKT

• Banging away at the paper
• Skim these
  • The bohemian bookshelf: supporting serendipitous book discoveries through information visualization
  • Discovery is never by chance: designing for (un)serendipity
  • Here’s the whole serendipity hierarchy: 
• ‘Kickoff’ meeting for the NOAA proof-of-concept

6:30 – ASRC MKT

• 10:00 status meeting
• Thinking about going to DC for lunch
• Matthew Zefferman
  • I am a quantitative social scientist who uses mathematical models and ethnographic field research to understand human ultrasociality – our ability to organize ourselves into societies capable of large-scale cooperation and large-scale conflict – especially in the contexts of war, political organization, and environmental sustainability.
  • I like the term ultrasociality, it captures some of the large-scale effects I’m looking at.
• NIMBios (Matthew Zefferman spent some time here) Has kind of a Max Planck vibe?
• Speaking of which, the logo for the Couzin Lab at Max Planck is a perfect explore/exploit icon: 
• Working on paper. Currently loading up Illustrator and IntelliJ to see which comes up first. Illustrator wins! I really need another monitor now…
  • Finished the methods/simulation section Starting on the pattern detection section

7:00 – 4:00 ASRC MKT

• • Look, someone else is finally working on my Master’s Thesis: Is Tribalism a Natural Malfunction?
  • Brian W came over last night to help me with LaTex Equations, specifically, this one, which is the orientation influence equation:
  • • Here’s the code that makes it:

      \vec{aoc}_x= \frac{\{
      \sum_{n=1}^{n = x-1} \vec{aop}_n (1 - \frac{\| \vec{app}_x - \vec{app_n} \| }{r}) + 
      \sum_{n=x+ 1}^{n = max} \vec{aop}_n (1 - \frac{\| \vec{app}_x - \vec{app}_n \| }{r})
      \mid (\|\vec{app}_x - \vec{app}_n \| < r)\}}{1-\sum_{n=1}^{n=max}[\|\vec{app}_n - \vec{app}_x\| < r]}

    • Given these conditions:
      • aoc is the current orientation vector
      • aop is the previous orientation vector
      • app is the current position
      • app is the previous position
      • r is the exploit radius
    • And this is the position update function: 
      • aop is the previous orientation vector
      • acp is the current position
      • app is the previous position
      • dt is elapsed time
    • Working on describing the high-dimensional slew using a diagram.

   

7:00 – 5:00 ASRC MKT

• Online, interactive LaTex text editor!!!
• Trust and Distrust in Online Fact-Checking Services
• Debunking: A Meta-Analysis of the Psychological Efficacy of Messages Countering Misinformation
  • This meta-analysis investigated the factors underlying effective messages to counter attitudes and beliefs based on misinformation. Because misinformation can lead to poor decisions about consequential matters and is persistent and difficult to correct, debunking it is an important scientific and public-policy goal. This meta-analysis (k = 52, N = 6,878) revealed large effects for presenting misinformation (ds = 2.41–3.08), debunking (ds = 1.14–1.33), and the persistence of misinformation in the face of debunking (ds = 0.75–1.06). Persistence was stronger and the debunking effect was weaker when audiences generated reasons in support of the initial misinformation. A detailed debunking message correlated positively with the debunking effect. Surprisingly, however, a detailed debunking message also correlated positively with the misinformation-persistence effect.
• The Impact of Crowds on News Engagement: A Reddit Case Study
  • Today, users are reading the news through social platforms. These platforms are built to facilitate crowd engagement, but not necessarily disseminate useful news to inform the masses. Hence, the news that is highly engaged with may not be the news that best informs. While predicting news popularity has been well studied, it has not been studied in the context of crowd manipulations. In this paper, we provide some preliminary results to a longer term project on crowd and platform manipulations of news and news popularity. In particular, we choose to study known features for predicting news popularity and how those features may change on reddit.com, a social platform used commonly for news aggregation. Along with this, we explore ways in which users can alter the perception of news through changing the title of an article. We find that news on reddit is predictable using previously studied sentiment and content features and that posts with titles changed by reddit users tend to be more popular than posts with the original article title.
  • fakenewsdata1

    This repository contains two independent news datasets used in the 2017 study: “This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire t…

• PHEME dataset of rumours and non-rumours
  • This dataset contains a collection of Twitter rumours and non-rumours posted during breaking news. The five breaking news provided with the dataset are as follows:
    * Charlie Hebdo: 458 rumours (22.0%) and 1,621 non-rumours (78.0%).
    * Ferguson: 284 rumours (24.8%) and 859 non-rumours (75.2%).
    * Germanwings Crash: 238 rumours (50.7%) and 231 non-rumours (49.3%).
    * Ottawa Shooting: 470 rumours (52.8%) and 420 non-rumours (47.2%).
    * Sydney Siege: 522 rumours (42.8%) and 699 non-rumours (57.2%).
•  SocInfo2017 Programme. Lots of good stuff
  • Christina Ting. Compression-Based Algorithms for Deception Detection
  • Jennifer Golbeck. The President on Twitter: A Characterization Study of @realDonaldTrump
  • Laura Wendlandt. Multimodal Analysis and Prediction of Latent User Dimensions
  • Babak Heydari. Why Groups Show Different Fairness Norms? The Interaction Topology Might Explain
  • Agus Sulistya. Inferring Spread of Readers’ Emotion Affected by Online News
  • Juan Sabuco. ABCE: A Python Library for Economic Agent-Based Modeling
  • Jaroslaw Jankowski. Seeds Buffering for Information Spreading Processes
  • Arkaitz Zubiaga. Exploiting Context for Rumour Detection in Social Media
  • Jisun An. Multidimensional Analysis of the News Consumption of Different Demographic Groups on a Nationwide Scale
  • David Jurgens. An Analysis of Individuals’ Behavior Change in Online Groups
  • Roy Lee. GitHub and Stack Overflow: Analyzing Developer Interests Across Multiple Social Collaborative Platforms
  • Tu Nguyen. On Early-Stage Debunking Rumors on Twitter: Leveraging the Wisdom of Weak Learners
  • Brian Pickering. Mediated Behavioural Change in Human-Machine Networks: Exploring Network Characteristics, Trust and Motivation
  • Jon Roozenbeek. I Read It on Reddit: Exploring the Role of Online Communities in the 2016 US Elections News Cycle
  • Nick Y. Zhang. What Can Software Tell Us About Media Coverage and Public Opinion?
• Ok, enough surfing, back to writing
  • Had to install MikTex and Texstudio to get at my papers. I thought I had done this on this computer but I guess not…
  • Got the major pieces copied over from PhysRevE. Methods needs a lot of work
  • Good progress! Done through the lit review, I made a scary looking equation, and the methods and results sections are shaping up.