Flexibility, Complexity, and Controllability in Large Scale Systems

System structure is a key determinant of system behavior. There is a particularly strong link between a system’s structure and its flexibility – it’s capacity to respond to changes. Often, adding flexibility entails adding complexity. In this paper, we propose measures for a system’s complexity that are complementary to existing flexibility measures. Furthermore, flexibility often comes at the cost of some measure of control over the system’s behavior. We therefore propose a metric for system controllability that is complementary to our flexibility metric

Analogies Between Complex Systems and Phases of Matter

The behavior of a complex system in a changing environment is strongly affected by the system's architecture. We present an analogy between the major phases of matter (solid, liquid, gas) and three major generic architectures of complex systems: tree structures, layered structures and grid networks. This analogy is realized using a graph-based formalism, with nodes and edges in a given configuration. Solid materials are akin to tree structures, especially when we consider that most solids actually have cracks. Solids with cracks between their components can be modeled by nodes (representing each component) and their interconnection, leading to a tree structured hierarchy. Gases made up of molecules can be modeled by nodes (the molecules) with local interconnections representing nearby molecules in space, thus forming a grid network. Liquids can form layers as in a mixture of oil and water. We represent this by connections that are densely horizontal within layers as well as sparsely vertical between layers. A key issue for complex systems is the ease by which they may be changed, which we call the system’s flexibility. Our definition of flexibility indicates that tree structures, like solids, are relatively inflexible and that grid networks, like gases, are extremely flexible, possibly leading to loss of control and chaotic behavior. Like liquids, layered systems are intermediate in flexibility and controllability. Solids, even with cracks, are relatively difficult to modify, whereas gases change internal form so quickly that they can only be constrained; not controlled. Liquids are intermediate in their ability to change form internally. Just as heating solids can lead to liquids, and heating liquids can result in gases, we shall present transformations in the interconnection structure of systems, analogous to heating, that change tree structures into layered ones and layered structures into networks

Gist and Verbatim in Narrative Memory

A major concern regarding the study of narratives regards how they are indexed and retrieved. This is a question which touches on the structure of human memory in general. Indeed, if narratives capture the substance of human thought, then data that we have already collected regarding human memory is of central importance to the computational study of narrative. Fuzzy Trace Theory assumes that memory for narrative is simultaneously stored at multiple levels of abstraction and, whenever possible, decision-makers interpret a stimulus qualitatively and therefore operate on a simple - typically categorical - "gist" representation. Here, we present a computational model of Fuzzy Trace Theory applied to explain the impact of changes in a narrative upon risky-choice framing effects. Overall, our theory predicts the outcome of 20 experimental effects using only three basic assumptions: 1) preference for lowest level of gist, that is, categorical processing; 2) decision options that fall within the same categorical description are then interpreted using finer-grained (ordinal or verbatim) distinctions; and 3) once the options are mentally represented, decision preferences are generated on the basis of simple positive vs. negative valences stored in long-term memory (e.g., positive value for human lives). A fourth assumption - that negatively-valenced decision options are preferentially converted to positive decision options - is used when categories are not otherwise comparable

Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues

The blurry line between nefarious fake news and protected-speech satire has been a notorious struggle for social media platforms. Further to the efforts of reducing exposure to misinformation on social media, purveyors of fake news have begun to masquerade as satire sites to avoid being demoted. In this work, we address the challenge of automatically classifying fake news versus satire. Previous work have studied whether fake news and satire can be distinguished based on language differences. Contrary to fake news, satire stories are usually humorous and carry some political or social message. We hypothesize that these nuances could be identified using semantic and linguistic cues. Consequently, we train a machine learning method using semantic representation, with a state-of-the-art contextual language model, and with linguistic features based on textual coherence metrics. Empirical evaluation attests to the merits of our approach compared to the language-based baseline and sheds light on the nuances between fake news and satire. As avenues for future work, we consider studying additional linguistic features related to the humor aspect, and enriching the data with current news events, to help identify a political or social message.Comment: Accepted to the 2nd Workshop on NLP for Internet Freedom (NLP4IF): Censorship, Disinformation, and Propaganda. Co-located with EMNLP-IJCNLP 201

Volatility of vaccine confidence.

Last week, the European Medicines Agency declared the AstraZeneca COVID-19 vaccine safe and effective, after several European Union member states had suspended its use because of blood clot concerns. Will the public trust this message? This week's news could help—a U.S. phase 3 clinical trial of the vaccine shows promising efficacy in preventing symptomatic COVID-19. But sentiments toward vaccines are volatile and reflect external events—such as recent concern about AstraZeneca's efficacy data—as well as internal emotions.</jats:p

Characterizing Trends in Human Papillomavirus Vaccine Discourse on Reddit (2007-2015): An Observational Study

Partial funding for Open Access provided by the UMD Libraries' Open Access Publishing Fund.Background: Despite the introduction of the human papillomavirus (HPV) vaccination as a preventive measure in 2006 for cervical and other cancers, uptake rates remain suboptimal, resulting in preventable cancer mortality. Social media, widely used for information seeking, can influence users’ knowledge and attitudes regarding HPV vaccination. Little is known regarding attitudes related to HPV vaccination on Reddit (a popular news aggregation site and online community), particularly related to cancer risk and sexual activity. Examining HPV vaccine–related messages on Reddit may provide insight into how HPV discussions are characterized on forums online and influence decision making related to vaccination. Objective: We observed how the HPV vaccine is characterized on Reddit over time and by user gender. Specifically, this study aimed to determine (1) if Reddit messages are more related to cancer risks or sexual behavior and (2) what other HPV vaccine–related discussion topics appear on Reddit. Methods: We gathered all public Reddit comments from January 2007 to September 2015. We manually annotated 400 messages to generate keywords and identify salient themes. We then measured the similarity between each comment and lists of keywords associated with sexual behavior and cancer risk using Latent Semantic Analysis (LSA). Next, we used Latent Dirichlet Allocation (LDA) to characterize remaining topics within the Reddit data. Results: We analyzed 22,729 messages containing the strings hpv or human papillomavirus and vaccin. LSA findings show that HPV vaccine discussions are significantly more related to cancer compared with sexual behavior from 2008 to 2015 (P<.001). We did not find a significant difference between genders in discussions of cancer and sexual activity (P>.05). LDA analyses demonstrated that although topics related to cancer risk and sexual activity were both frequently discussed (16.1% and 14.5% of word tokens, respectively), the majority of online discussions featured other topics. The most frequently discussed topic was politics associated with the vaccine (17.2%). Other topics included HPV disease and/or immunity (13.5%), the HPV vaccine schedule (11.5%), HPV vaccine side effects (9.7%), hyperlinks to outside sources (9.1%), and the risks and benefit of HPV vaccination (8.5%). Conclusions: Reddit discourse on HPV vaccine encompasses a broad range of topics among men and women, with HPV political debates and cancer risk making up the plurality of the discussion. Our findings demonstrated that women and men both discussed HPV, highlighting that Reddit users do not perceive HPV as an issue that only pertains to women. Given the increasing use of social media as a source of health information, these results can inform the development of targeted online health communication strategies to promote HPV vaccination to young adult users of Reddit. Analyzing online discussions on Reddit can inform health communication efforts by identifying relevant, important HPV-related topics among online communities