1. Socio-Digital Influence Attack Models and Deterrence (FA9550-15-1-0003) PI: Tim Weninger (University of Notre Dame; Computer Science and Engineering) AFOSR Program Review: T rust & Influence May 11-15, 2015, USAF Academy, CO.

2. The Idea: Determine the influence and impact that social news and networks have on user behavior. …and find countermeasures against social media manipulation.

3. Hivemind Experiment What effects does early voting have on later voting? Does quality matter?

4. Hivemind Experiment Final scores for artificially, randomly up-treated posts, down-treated posts, and scores for untreated posts in the control group are shown. Red inner error bars show the standard error of the mean; black outer error bars show the 95% confidence interval. (a) shows the scores in the heavily skewed full distribution. When the highest 1% of scores are removed as in (b), the score distribution becomes much less skewed resulting in tighter error bounds, which further result in significant increases for up-treated posts and significant decreases for down-treated posts when compared to the control group. Paper under review

5. Hivemind Experiment Final scores for artificially, randomly up-treated posts, down-treated posts, and scores for untreated posts in the control group separated into their respective treatment delay intervals. Horizontal lines show the overall mean of each treatment group. The top 1% of scores were removed to un-skew the score distribution. These results show that treatment delay had little effect on the mean final score. Paper under review

6. Hivemind Experiment The middle 9 deciles of up-treated, down-treated and control group posts are shown according to their interval times. These results show that most posts receive a median score of 2 or less, and that the treatment has the most effect in the higher deciles of the score distribution. Paper under review

7. Hivemind Experiment The probability of a post receiving a corresponding score by treatment type. The inset graph shows the complete probability distribution function. The outer graph shows the probability of a post receiving scores between 500 and 2000 an approximation for trending or frontpage posts. Up-treated posts are 24% more likely to reach 2000 votes than the control group. Paper under review

8. Hivemind Experiment Mean scores of down-treated, control group and up-treated posts shown with 95% confidence intervals on the top 8 most active subreddits. Paper under review

9. Hivemind Experiment Update on Vote gathering Reddit won’t allow it, some work already done. I (mistakenly) spoke with Reddit cofounder and interim-CEO, they changed the mechanisms. No experiment like this is possible any longer. Paper under review

10. Patterns of Natural Human Navigation Model human navigation processes through knowledge networks Use these models to create knowledge repositories better suited for human browsing Paper under review

11. Patterns of Natural Human Navigation Paper under review Scatterplots comparing path lengths for each path navigation model. Only 500 random points are plotted in each subfigure for efficient document rendering. Slope of linear regression line indicates correlation strength.

12. Patterns of Natural Human Navigation Paper under review CatPath distance-to-go as a function of (a) PPR, and (b) human path length- to-go with standard error (red) and 95% condence intervals (black)

13. Patterns of Natural Human Navigation Paper under review Distribution of path lengths for various models. PPR does not result in a path length; rather the PPR score between the source and the destination nodes discretized into 30 equal size bins for comparison-sake.

14. Publications, Awards, Patents, or Transitions Attributed to the Grant Baoxu Shi and Tim Weninger Mining Interesting Meta-Paths from Complex Heterogeneous Information Networks. International Conference on Data Mining (ICDM) Designing Market of Data, Shenzhen, China, December 14-17, 2014. Tim Weninger. An Exploration of Submissions and Discussions in Social News - Mining Collective Intelligence of Reddit. Social Network Analysis and Mining (SNAM), 4:173 (2014). Invited Speaker - Greater Chicago Area System Research Workshop at UIC Forum in Chicago. Apr 2015 Keynote - International Symposium on Occupational Exposure to deliver keynote on Data Science. Jan 2015 Invited Fellow - United States National Academies of Science as Fellow of the National Academies Keck Futures Initiative. Nov 2014. Invited Speaker - MetaKnowledge Meeting in Asilomar, CA August 2014. Speaker - KDD Conference in New York City August 2014. Speaker -WebSci Conference in Bloomington, IN. July 2014

15. Project Summary Research Objectives: Identify and measure sources of influence corruption and their effect on global outcomes Create models of trust and influence propagation in social media and networks. Key Findings: Vote influence is real and is happening, but effects are not as bad as it could be. Trust and influence may be accurately modeled in networks bidirectionally. Technical Approach: In vivo studies of social media Statistical and Bayesian models of human behavior. Benefits to the wider academic or DoD community: Preliminary measurements of a new type of influence attack. Bidirectional network influence model. Project Start Date: Jan 1, 2015 Project End Date: Dec 31, 2017

16. Thank you tweninge@nd.edu