Selected Readings on Sentiment Analysis

Curated on Posted on by sophie

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of sentiment analysis was originally published in 2014.

Sentiment Analysis is a field of Computer Science that uses techniques from natural language processing, computational linguistics, and machine learning to predict subjective meaning from text. The term opinion mining is often used interchangeably with Sentiment Analysis, although it is technically a subfield focusing on the extraction of opinions (the umbrella under which sentiment, evaluation, appraisal, attitude, and emotion all lie).

The rise of Web 2.0 and increased information flow has led to an increase in interest towards Sentiment Analysis — especially as applied to social networks and media. Events causing large spikes in media — such as the 2012 Presidential Election Debates — are especially ripe for analysis. Such analyses raise a variety of implications for the future of crowd participation, elections, and governance.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Choi, Eunsol et al. “Hedge detection as a lens on framing in the GMO debates: a position paper.” Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics 13 Jul. 2012: 70-79. http://bit.ly/1wweftP

  • Understanding the ways in which participants in public discussions frame their arguments is important for understanding how public opinion is formed. This paper adopts the position that it is time for more computationally-oriented research on problems involving framing. In the interests of furthering that goal, the authors propose the following question: In the controversy regarding the use of genetically-modified organisms (GMOs) in agriculture, do pro- and anti-GMO articles differ in whether they choose to adopt a more “scientific” tone?
  • Prior work on the rhetoric and sociology of science suggests that hedging may distinguish popular-science text from text written by professional scientists for their colleagues. The paper proposes a detailed approach to studying whether hedge detection can be used to understand scientific framing in the GMO debates, and provides corpora to facilitate this study. Some of the preliminary analyses suggest that hedges occur less frequently in scientific discourse than in popular text, a finding that contradicts prior assertions in the literature.

Michael, Christina, Francesca Toni, and Krysia Broda. “Sentiment analysis for debates.” (Unpublished MSc thesis). Department of Computing, Imperial College London (2013). http://bit.ly/Wi86Xv

  • This project aims to expand on existing solutions used for automatic sentiment analysis on text in order to capture support/opposition and agreement/disagreement in debates. In addition, it looks at visualizing the classification results for enhancing the ease of understanding the debates and for showing underlying trends. Finally, it evaluates proposed techniques on an existing debate system for social networking.

Murakami, Akiko, and Rudy Raymond. “Support or oppose?: classifying positions in online debates from reply activities and opinion expressions.” Proceedings of the 23rd International Conference on Computational Linguistics: Posters 23 Aug. 2010: 869-875. https://bit.ly/2Eicfnm

  • In this paper, the authors propose a method for the task of identifying the general positions of users in online debates, i.e., support or oppose the main topic of an online debate, by exploiting local information in their remarks within the debate. An online debate is a forum where each user posts an opinion on a particular topic while other users state their positions by posting their remarks within the debate. The supporting or opposing remarks are made by directly replying to the opinion, or indirectly to other remarks (to express local agreement or disagreement), which makes the task of identifying users’ general positions difficult.
  • A prior study has shown that a link-based method, which completely ignores the content of the remarks, can achieve higher accuracy for the identification task than methods based solely on the contents of the remarks. In this paper, it is shown that utilizing the textual content of the remarks into the link-based method can yield higher accuracy in the identification task.

Pang, Bo, and Lillian Lee. “Opinion mining and sentiment analysis.” Foundations and trends in information retrieval 2.1-2 (2008): 1-135. http://bit.ly/UaCBwD

  • This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. Its focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. It includes material on summarization of evaluative text and on broader issues regarding privacy, manipulation, and economic impact that the development of opinion-oriented information-access services gives rise to. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided.

Ranade, Sarvesh et al. “Online debate summarization using topic directed sentiment analysis.” Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining 11 Aug. 2013: 7. http://bit.ly/1nbKtLn

  • Social networking sites provide users a virtual community interaction platform to share their thoughts, life experiences and opinions. Online debate forum is one such platform where people can take a stance and argue in support or opposition of debate topics. An important feature of such forums is that they are dynamic and grow rapidly. In such situations, effective opinion summarization approaches are needed so that readers need not go through the entire debate.
  • This paper aims to summarize online debates by extracting highly topic relevant and sentiment rich sentences. The proposed approach takes into account topic relevant, document relevant and sentiment based features to capture topic opinionated sentences. ROUGE (Recall-Oriented Understudy for Gisting Evaluation, which employ a set of metrics and a software package to compare automatically produced summary or translation against human-produced onces) scores are used to evaluate the system. This system significantly outperforms several baseline systems and show improvement over the state-of-the-art opinion summarization system. The results verify that topic directed sentiment features are most important to generate effective debate summaries.

Schneider, Jodi. “Automated argumentation mining to the rescue? Envisioning argumentation and decision-making support for debates in open online collaboration communities.” http://bit.ly/1mi7ztx

  • Argumentation mining, a relatively new area of discourse analysis, involves automatically identifying and structuring arguments. Following a basic introduction to argumentation, the authors describe a new possible domain for argumentation mining: debates in open online collaboration communities.
  • Based on our experience with manual annotation of arguments in debates, the authors propose argumentation mining as the basis for three kinds of support tools, for authoring more persuasive arguments, finding weaknesses in others’ arguments, and summarizing a debate’s overall conclusions.

Crowd-Sourced Augmented Realities: Social Media and the Power of Digital Representation

Curated on Posted on by Stefaan Verhulst

Pre-publication version of a chapter by Matthew Zook, Mark Graham and  Andrew Boulton  in S. Mains, J. Cupples, and C. Lukinbeal. Mediated Geographies/Geographies of Media. Springer Science International Handbooks in Human Geography, (Forthcoming): “A key and distinguishing feature of society today is that its increasingly documented by crowd-sourced social media discourse about public experiences. Much of this social media content is geo-referenced and exists in layers of information draped over the physical world, invisible to the naked eye but accessible to range of digital (and often) mobile devices. When we access these information layers, they mediate the mundane practices of everyday life, (e.g., What or who is nearby? How do I move from point A to B) through the creation of augmented realities, i.e., unstable, context dependent representations of places brought temporary into being by combining the space of material and virtual experience.
These augmented realities, as particular representations of locations, places and events, are vigorously promoted or contested and thus become important spots in which power is exercised, much in the same way that maps have long had power to reinforce or challenge the status quo. However, because many of the processes and practices behind the creation of augmented realities are unseen, its power is often overlooked in the process of representation or place-making. This paper highlights the points at which power acts and demonstrate that all representations of place – including augmented realities derived from social media – are products of and productive of, social relationships and associated power relations.”
Building upon a case study of Abbottabad, Pakistan after the raid on Osama bin Laden’s compound we construct a four-part typology of the power relations emerging from social practices that enact augmented realities. These include: Distributed power, the complex and socially/spatially distributed authorship of user-generated geospatial content; Communication power, the ways in which particular representations gain prominence; language is a particularly key variable; Code power, the autonomy of software code to regulate actions, or mediate content, or ordering representations in particular ways; and Timeless power, the ways in which digital representations of place reconfigure temporal relationships, particularly sequence and duration, between people and events.

A framework for measuring smart cities

Curated on Posted on by Stefaan Verhulst
Paper by Félix Herrera Priano and Cristina Fajardo Guerra for the Proceedings of the 15th Annual International Conference on Digital Government Research: “Smart cities are an international phenomenon. Many cities are actively working to build or transform their models toward that of a Smart City. There is constant research and reports devoted to measuring the intelligence of cities through establishing specific methodologies and indicators (grouped by various criteria).
We believe the subject lacks a certain uniformity, which we aim to redress in this paper by suggesting a framework for properly measuring the smart level of a city.
Cities are complex and heterogeneous structures, which complicates comparisons between them. To address this we propose an N–dimensional measurement framework where each level or dimension supplies information of interest that is evaluated independently. As a result, the measure of a city’s intelligence is the result of the evaluations obtained for each of these levels.
To this end, we have typified the transformation (city to smart city) and the measurement (smart city ranking) processes.”

The People’s Platform

Curated on Posted on by Stefaan Verhulst

Book Review by Tim Wu in the New York Times: “Astra Taylor is a documentary filmmaker who has described her work as the “steamed broccoli” in our cultural diet. Her last film, “Examined Life,” depicted philosophers walking around and talking about their ideas. She’s the kind of creative person who was supposed to benefit when the Internet revolution collapsed old media hierarchies. But two decades since that revolution began, she’s not impressed: “We are at risk of starving in the midst of plenty,” Taylor writes. “Free culture, like cheap food, incurs hidden costs.” Instead of serving as the great equalizer, the web has created an abhorrent cultural feudalism. The creative masses connect, create and labor, while Google, Facebook and Amazon collect the cash.
Taylor’s thesis is simply stated. The pre-Internet cultural industry, populated mainly by exploitative conglomerates, was far from perfect, but at least the ancien régime felt some need to cultivate cultural institutions, and to pay for talent at all levels. Along came the web, which swept away hierarchies — as well as paychecks, leaving behind creators of all kinds only the chance to be fleetingly “Internet famous.” And anyhow, she says, the web never really threatened to overthrow the old media’s upper echelons, whether defined as superstars, like Beyoncé, big broadcast television shows or Hollywood studios. Instead, it was the cultural industry’s middle ­classes that have been wiped out and replaced by new cultural plantations ruled over by the West Coast aggregators.
It is hard to know if the title, “The People’s Platform,” is aspirational or sarcastic, since Taylor believes the classless aura of the web masks an unfair power structure. “Open systems can be starkly inegalitarian,” she says, arguing that the web is afflicted by what the feminist scholar Jo Freeman termed a “tyranny of structurelessness.” Because there is supposedly no hierarchy, elites can happily deny their own existence. (“We just run a platform.”) But the effects are real: The web has reduced professional creators to begging for scraps of attention from a spoiled public, and forced creators to be their own brand.
…
The tech industry might be tempted to dismiss Taylor’s arguments as merely a version of typewriter manufacturers’ complaints circa 1984, but that would be a mistake. “The People’s Platform” should be taken as a challenge by the new media that have long claimed to be improving on the old order. Can they prove they are capable of supporting a sustainable cultural ecosystem, in a way that goes beyond just hosting parties at the Sundance Film ­Festival?
We see some of this in the tech firms that have begun to pay for original content, as with Netflix’s investments in projects like “Orange Is the New Black.” It’s also worth pointing out that the support of culture is actually pretty cheap. Consider the nonprofit ProPublica, which employs investigative journalists, and has already won two Pulitzers, all on a budget of just over $10 million a year. That kind of money is a rounding error for much of Silicon Valley, where losing billions on bad acquisitions is routinely defended as “strategic.” If Google, Apple, Facebook and Amazon truly believe they’re better than the old guard, let’s see it.”
See : THE PEOPLE’S PLATFORM. Taking Back Power and Culture in the Digital Age By Astra Taylor, 276 pp. Metropolitan Books/Henry Holt & Company.

Brief survey of crowdsourcing for data mining

Curated on Posted on by Stefaan Verhulst

Paper by Guo Xintong,  Wang Hongzhi, Yangqiu Song, and Gao Hong in Expert Systems with Applications: “Crowdsourcing allows large-scale and flexible invocation of human input for data gathering and analysis, which introduces a new paradigm of data mining process. Traditional data mining methods often require the experts in analytic domains to annotate the data. However, it is expensive and usually takes a long time. Crowdsourcing enables the use of heterogeneous background knowledge from volunteers and distributes the annotation process to small portions of efforts from different contributions. This paper reviews the state-of-the-arts on the crowdsourcing for data mining in recent years. We first review the challenges and opportunities of data mining tasks using crowdsourcing, and summarize the framework of them. Then we highlight several exemplar works in each component of the framework, including question designing, data mining and quality control. Finally, we conclude the limitation of crowdsourcing for data mining and suggest related areas for future research.

Incentivizing Peer Review

Curated on Posted on by Stefaan Verhulst

in Wired on “The Last Obstacle for Open Access Science: The Galapagos Islands’ Charles Darwin Foundation runs on an annual operating budget of about $3.5 million. With this money, the center conducts conservation research, enacts species-saving interventions, and provides educational resources about the fragile island ecosystems. As a science-based enterprise whose work would benefit greatly from the latest research findings on ecological management, evolution, and invasive species, there’s one glaring hole in the Foundation’s budget: the $800,000 it would cost per year for subscriptions to leading academic journals.
According to Richard Price, founder and CEO of Academia.edu, this episode is symptomatic of a larger problem. “A lot of research centers” – NGOs, academic institutions in the developing world – “are just out in the cold as far as access to top journals is concerned,” says Price. “Research is being commoditized, and it’s just another aspect of the digital divide between the haves and have-nots.”
 
Academia.edu is a key player in the movement toward open access scientific publishing, with over 11 million participants who have uploaded nearly 3 million scientific papers to the site. It’s easy to understand Price’s frustration with the current model, in which academics donate their time to review articles, pay for the right to publish articles, and pay for access to articles. According to Price, journals charge an average of $4000 per article: $1500 for production costs (reformatting, designing), $1500 to orchestrate peer review (labor costs for hiring editors, administrators), and $1000 of profit.
“If there were no legacy in the scientific publishing industry, and we were looking at the best way to disseminate and view scientific results,” proposes Price, “things would look very different. Our vision is to build a complete replacement for scientific publishing,” one that would allow budget-constrained organizations like the CDF full access to information that directly impacts their work.
But getting to a sustainable new world order requires a thorough overhaul of academic publishing industry. The alternative vision – of “open science” – has two key properties: the uninhibited sharing of research findings, and a new peer review system that incorporates the best of the scientific community’s feedback. Several groups have made progress on the former, but the latter has proven particularly difficult given the current incentive structure. The currency of scientific research is the number of papers you’ve published and their citation counts – the number of times other researchers have referred to your work in their own publications. The emphasis is on creation of new knowledge – a worthy goal, to be sure – but substantial contributions to the quality, packaging, and contextualization of that knowledge in the form of peer review goes largely unrecognized. As a result, researchers view their role as reviewers as a chore, a time-consuming task required to sustain the ecosystem of research dissemination.
“Several experiments in this space have tried to incorporate online comment systems,” explains Price, “and the result is that putting a comment box online and expecting high quality comments to flood in is just unrealistic. My preference is to come up with a system where you’re just as motivated to share your feedback on a paper as you are to share your own findings.” In order to make this lofty aim a reality, reviewers’ contributions would need to be recognized. “You need something more nuanced, and more qualitative,” says Price. “For example, maybe you gather reputation points from your community online.” Translating such metrics into tangible benefits up the food chain – hirings, tenure decisions, awards – is a broader community shift that will no doubt take time.
A more iterative peer review process could allow the community to better police faulty methods by crowdsourcing their evaluation. “90% of scientific studies are not reproducible,” claims Price; a problem that is exacerbated by the strong bias toward positive results. Journals may be unlikely to publish methodological refutations, but a flurry of well-supported comments attached to a paper online could convince the researchers to marshal more convincing evidence. Typically, this sort of feedback cycle takes years….”

Social Network Sites as a Mode to Collect Health Data: A Systematic Review

Curated on Posted on by Stefaan Verhulst

New paper by Fahdah Alshaikh, et al, in J Med Internet Research: “Background: To date, health research literature has focused on social network sites (SNS) either as tools to deliver health care, to study the effect of these networks on behavior, or to analyze Web health content. Less is known about the effectiveness of these sites as a method for collecting data for health research and the means to use such powerful tools in health research.
Objective: The objective of this study was to systematically review the available literature and explore the use of SNS as a mode of collecting data for health research. The review aims to answer four questions: Does health research employ SNS as method for collecting data? Is data quality affected by the mode of data collection? What types of participants were reached by SNS? What are the strengths and limitations of SNS?
Methods: The literature was reviewed systematically in March 2013 by searching the databases MEDLINE, Embase, and PsycINFO, using the Ovid and PubMed interface from 1996 to the third week of March 2013. The search results were examined by 2 reviewers, and exclusion, inclusion, and quality assessment were carried out based on a pre-set protocol.
Results: The inclusion criteria were met by 10 studies and results were analyzed descriptively to answer the review questions. There were four main results. (1) SNS have been used as a data collection tool by health researchers; all but 1 of the included studies were cross-sectional and quantitative. (2) Data quality indicators that were reported include response rate, cost, timeliness, missing data/completion rate, and validity. However, comparison was carried out only for response rate and cost as it was unclear how other reported indicators were measured. (3) The most targeted population were females and younger people. (4) All studies stated that SNS is an effective recruitment method but that it may introduce a sampling bias.
Conclusions: SNS has a role in health research, but we need to ascertain how to use it effectively without affecting the quality of research. The field of SNS is growing rapidly, and it is necessary to take advantage of the strengths of this tool and to avoid its limitations by effective research design. This review provides an important insight for scholars who plan to conduct research using SNS.”

Crowdsourcing Parking Lot Occupancy using a Mobile Phone Application

Curated on Posted on by Stefaan Verhulst

Paper by Davami, Erfan; Sukthankar, Gita available at ASE@360: “Participatory sensing is a specialized form of crowdsourcing for mobile devices in which the users act as sensors to report on local environmental conditions. • This poster describes the process of prototyping a mobile phone crowdsourcing app for monitoring parking availability on a large university campus. • We present a case study of how an agent-based urban model can be used to perform a sensitivity analysis of the comparative susceptibility of different data fusion paradigms to potentially troublesome user behaviors: 1. Poor user enrollment, 2. Infrequent usage, 3. A preponderance of untrustworthy users.”

The open data imperative

Curated on Posted on by Stefaan Verhulst

Paper by Geoffrey Boulton in Insights: the UKSG journal: “The information revolution of recent decades is a world historical event that is changing the lives of individuals, societies and economies and with major implications for science, research and learning. It offers profound opportunities to explore phenomena that were hitherto beyond our power to resolve, and at the same time is undermining the process whereby concurrent publication of scientific concept and evidence (data) permitted scrutiny, replication and refutation and that has been the bedrock of scientific progress and of ‘self-correction’ since the inception of the first scientific journals in the 17th century. Open publication, release and sharing of data are vital habits that need to be redefined and redeveloped for the modern age by the research community if it is to exploit technological opportunities, maintain self-correction and maximize the contribution of research to human understanding and welfare.”

Selected Readings on Crowdsourcing Expertise

Curated on Posted on by Andrew Young

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of crowdsourcing was originally published in 2014.

Crowdsourcing enables leaders and citizens to work together to solve public problems in new and innovative ways. New tools and platforms enable citizens with differing levels of knowledge, expertise, experience and abilities to collaborate and solve problems together. Identifying experts, or individuals with specialized skills, knowledge or abilities with regard to a specific topic, and incentivizing their participation in crowdsourcing information, knowledge or experience to achieve a shared goal can enhance the efficiency and effectiveness of problem solving.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Börner, Katy, Michael Conlon, Jon Corson-Rikert, and Ying Ding. “VIVO: A Semantic Approach to Scholarly Networking and Discovery.” Synthesis Lectures on the Semantic Web: Theory and Technology 2, no. 1 (October 17, 2012): 1–178. http://bit.ly/17huggT.

  • This e-book “provides an introduction to VIVO…a tool for representing information about research and researchers — their scholarly works, research interests, and organizational relationships.”
  • VIVO is a response to the fact that, “Information for scholars — and about scholarly activity — has not kept pace with the increasing demands and expectations. Information remains siloed in legacy systems and behind various access controls that must be licensed or otherwise negotiated before access. Information representation is in its infancy. The raw material of scholarship — the data and information regarding previous work — is not available in common formats with common semantics.”
  • Providing access to structured information on the work and experience of a diversity of scholars enables improved expert finding — “identifying and engaging experts whose scholarly works is of value to one’s own. To find experts, one needs rich data regarding one’s own work and the work of potential related experts. The authors argue that expert finding is of increasing importance since, “[m]ulti-disciplinary and inter-disciplinary investigation is increasingly required to address complex problems. 

Bozzon, Alessandro, Marco Brambilla, Stefano Ceri, Matteo Silvestri, and Giuliano Vesci. “Choosing the Right Crowd: Expert Finding in Social Networks.” In Proceedings of the 16th International Conference on Extending Database Technology, 637–648. EDBT  ’13. New York, NY, USA: ACM, 2013. http://bit.ly/18QbtY5.

  • This paper explores the challenge of selecting experts within the population of social networks by considering the following problem: “given an expertise need (expressed for instance as a natural language query) and a set of social network members, who are the most knowledgeable people for addressing that need?”
  • The authors come to the following conclusions:
    • “profile information is generally less effective than information about resources that they directly create, own or annotate;
    • resources which are produced by others (resources appearing on the person’s Facebook wall or produced by people that she follows on Twitter) help increasing the assessment precision;
    • Twitter appears the most effective social network for expertise matching, as it very frequently outperforms all other social networks (either combined or alone);
    • Twitter appears as well very effective for matching expertise in domains such as computer engineering, science, sport, and technology & games, but Facebook is also very effective in fields such as locations, music, sport, and movies & tv;
    • surprisingly, LinkedIn appears less effective than other social networks in all domains (including computer science) and overall.”

Brabham, Daren C. “The Myth of Amateur Crowds.” Information, Communication & Society 15, no. 3 (2012): 394–410. http://bit.ly/1hdnGJV.

  • Unlike most of the related literature, this paper focuses on bringing attention to the expertise already being tapped by crowdsourcing efforts rather than determining ways to identify more dormant expertise to improve the results of crowdsourcing.
  • Brabham comes to two central conclusions: “(1) crowdsourcing is discussed in the popular press as a process driven by amateurs and hobbyists, yet empirical research on crowdsourcing indicates that crowds are largely self-selected professionals and experts who opt-in to crowdsourcing arrangements; and (2) the myth of the amateur in crowdsourcing ventures works to label crowds as mere hobbyists who see crowdsourcing ventures as opportunities for creative expression, as entertainment, or as opportunities to pass the time when bored. This amateur/hobbyist label then undermines the fact that large amounts of real work and expert knowledge are exerted by crowds for relatively little reward and to serve the profit motives of companies. 

Dutton, William H. Networking Distributed Public Expertise: Strategies for Citizen Sourcing Advice to Government. One of a Series of Occasional Papers in Science and Technology Policy, Science and Technology Policy Institute, Institute for Defense Analyses, February 23, 2011. http://bit.ly/1c1bpEB.

  • In this paper, a case is made for more structured and well-managed crowdsourcing efforts within government. Specifically, the paper “explains how collaborative networking can be used to harness the distributed expertise of citizens, as distinguished from citizen consultation, which seeks to engage citizens — each on an equal footing.” Instead of looking for answers from an undefined crowd, Dutton proposes “networking the public as advisors” by seeking to “involve experts on particular public issues and problems distributed anywhere in the world.”
  • Dutton argues that expert-based crowdsourcing can be successfully for government for a number of reasons:
    • Direct communication with a diversity of independent experts
    • The convening power of government
    • Compatibility with open government and open innovation
    • Synergy with citizen consultation
    • Building on experience with paid consultants
    • Speed and urgency
    • Centrality of documents to policy and practice.
  • He also proposes a nine-step process for government to foster bottom-up collaboration networks:
    • Do not reinvent the technology
    • Focus on activities, not the tools
    • Start small, but capable of scaling up
    • Modularize
    • Be open and flexible in finding and going to communities of experts
    • Do not concentrate on one approach to all problems
    • Cultivate the bottom-up development of multiple projects
    • Experience networking and collaborating — be a networked individual
    • Capture, reward, and publicize success.

Goel, Gagan, Afshin Nikzad and Adish Singla. “Matching Workers with Tasks: Incentives in Heterogeneous Crowdsourcing Markets.” Under review by the International World Wide Web Conference (WWW). 2014. http://bit.ly/1qHBkdf

  • Combining the notions of crowdsourcing expertise and crowdsourcing tasks, this paper focuses on the challenge within platforms like Mechanical Turk related to intelligently matching tasks to workers.
  • The authors’ call for more strategic assignment of tasks in crowdsourcing markets is based on the understanding that “each worker has certain expertise and interests which define the set of tasks she can and is willing to do.”
  • Focusing on developing meaningful incentives based on varying levels of expertise, the authors sought to create a mechanism that, “i) is incentive compatible in the sense that it is truthful for agents to report their true cost, ii) picks a set of workers and assigns them to the tasks they are eligible for in order to maximize the utility of the requester, iii) makes sure total payments made to the workers doesn’t exceed the budget of the requester.

Gubanov, D., N. Korgin, D. Novikov and A. Kalkov. E-Expertise: Modern Collective Intelligence. Springer, Studies in Computational Intelligence 558, 2014. http://bit.ly/U1sxX7

  • In this book, the authors focus on “organization and mechanisms of expert decision-making support using modern information and communication technologies, as well as information analysis and collective intelligence technologies (electronic expertise or simply e-expertise).”
  • The book, which “addresses a wide range of readers interested in management, decision-making and expert activity in political, economic, social and industrial spheres, is broken into five chapters:
    • Chapter 1 (E-Expertise) discusses the role of e-expertise in decision-making processes. The procedures of e-expertise are classified, their benefits and shortcomings are identified, and the efficiency conditions are considered.
    • Chapter 2 (Expert Technologies and Principles) provides a comprehensive overview of modern expert technologies. A special emphasis is placed on the specifics of e-expertise. Moreover, the authors study the feasibility and reasonability of employing well-known methods and approaches in e-expertise.
    • Chapter 3 (E-Expertise: Organization and Technologies) describes some examples of up-to-date technologies to perform e-expertise.
    • Chapter 4 (Trust Networks and Competence Networks) deals with the problems of expert finding and grouping by information and communication technologies.
    • Chapter 5 (Active Expertise) treats the problem of expertise stability against any strategic manipulation by experts or coordinators pursuing individual goals.

Holst, Cathrine. “Expertise and Democracy.” ARENA Report No 1/14, Center for European Studies, University of Oslo. http://bit.ly/1nm3rh4

  • This report contains a set of 16 papers focused on the concept of “epistocracy,” meaning the “rule of knowers.” The papers inquire into the role of knowledge and expertise in modern democracies and especially in the European Union (EU). Major themes are: expert-rule and democratic legitimacy; the role of knowledge and expertise in EU governance; and the European Commission’s use of expertise.
    • Expert-rule and democratic legitimacy
      • Papers within this theme concentrate on issues such as the “implications of modern democracies’ knowledge and expertise dependence for political and democratic theory.” Topics include the accountability of experts, the legitimacy of expert arrangements within democracies, the role of evidence in policy-making, how expertise can be problematic in democratic contexts, and “ethical expertise” and its place in epistemic democracies.
    • The role of knowledge and expertise in EU governance
      • Papers within this theme concentrate on “general trends and developments in the EU with regard to the role of expertise and experts in political decision-making, the implications for the EU’s democratic legitimacy, and analytical strategies for studying expertise and democratic legitimacy in an EU context.”
    • The European Commission’s use of expertise
      • Papers within this theme concentrate on how the European Commission uses expertise and in particular the European Commission’s “expertgroup system.” Topics include the European Citizen’s Initiative, analytic-deliberative processes in EU food safety, the operation of EU environmental agencies, and the autonomy of various EU agencies.

King, Andrew and Karim R. Lakhani. “Using Open Innovation to Identify the Best Ideas.” MIT Sloan Management Review, September 11, 2013. http://bit.ly/HjVOpi.

  • In this paper, King and Lakhani examine different methods for opening innovation, where, “[i]nstead of doing everything in-house, companies can tap into the ideas cloud of external expertise to develop new products and services.”
  • The three types of open innovation discussed are: opening the idea-creation process, competitions where prizes are offered and designers bid with possible solutions; opening the idea-selection process, ‘approval contests’ in which outsiders vote to determine which entries should be pursued; and opening both idea generation and selection, an option used especially by organizations focused on quickly changing needs.

Long, Chengjiang, Gang Hua and Ashish Kapoor. “Active Visual Recognition with Expertise Estimation in Crowdsourcing.” 2013 IEEE International Conference on Computer Vision. December 2013. http://bit.ly/1lRWFur.

  • This paper is focused on improving the crowdsourced labeling of visual datasets from platforms like Mechanical Turk. The authors note that, “Although it is cheap to obtain large quantity of labels through crowdsourcing, it has been well known that the collected labels could be very noisy. So it is desirable to model the expertise level of the labelers to ensure the quality of the labels. The higher the expertise level a labeler is at, the lower the label noises he/she will produce.”
  • Based on the need for identifying expert labelers upfront, the authors developed an “active classifier learning system which determines which users to label which unlabeled examples” from collected visual datasets.
  • The researchers’ experiments in identifying expert visual dataset labelers led to findings demonstrating that the “active selection” of expert labelers is beneficial in cutting through the noise of crowdsourcing platforms.

Noveck, Beth Simone. “’Peer to Patent’: Collective Intelligence, Open Review, and Patent Reform.” Harvard Journal of Law & Technology 20, no. 1 (Fall 2006): 123–162. http://bit.ly/HegzTT.

  • This law review article introduces the idea of crowdsourcing expertise to mitigate the challenge of patent processing. Noveck argues that, “access to information is the crux of the patent quality problem. Patent examiners currently make decisions about the grant of a patent that will shape an industry for a twenty-year period on the basis of a limited subset of available information. Examiners may neither consult the public, talk to experts, nor, in many cases, even use the Internet.”
  • Peer-to-Patent, which launched three years after this article, is based on the idea that, “The new generation of social software might not only make it easier to find friends but also to find expertise that can be applied to legal and policy decision-making. This way, we can improve upon the Constitutional promise to promote the progress of science and the useful arts in our democracy by ensuring that only worth ideas receive that ‘odious monopoly’ of which Thomas Jefferson complained.”

Ober, Josiah. “Democracy’s Wisdom: An Aristotelian Middle Way for Collective Judgment.” American Political Science Review 107, no. 01 (2013): 104–122. http://bit.ly/1cgf857.

  • In this paper, Ober argues that, “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.”
  • Ober describes an approach to decision-making that aggregates expertise across multiple domains. This “Relevant Expertise Aggregation (REA) enables a body of minimally competent voters to make superior choices among multiple options, on matters of common interest.”

Sims, Max H., Jeffrey Bigham, Henry Kautz and Marc W. Halterman. “Crowdsourcing medical expertise in near real time.” Journal of Hospital Medicine 9, no. 7, July 2014. http://bit.ly/1kAKvq7.

  • In this article, the authors discuss the develoment of a mobile application called DocCHIRP, which was developed due to the fact that, “although the Internet creates unprecedented access to information, gaps in the medical literature and inefficient searches often leave healthcare providers’ questions unanswered.”
  • The DocCHIRP pilot project used a “system of point-to-multipoint push notifications designed to help providers problem solve by crowdsourcing from their peers.”
  • Healthcare providers (HCPs) sought to gain intelligence from the crowd, which included 85 registered users, on questions related to medication, complex medical decision making, standard of care, administrative, testing and referrals.
  • The authors believe that, “if future iterations of the mobile crowdsourcing applications can address…adoption barriers and support the organic growth of the crowd of HCPs,” then “the approach could have a positive and transformative effect on how providers acquire relevant knowledge and care for patients.”

Spina, Alessandro. “Scientific Expertise and Open Government in the Digital Era: Some Reflections on EFSA and Other EU Agencies.” in Foundations of EU Food Law and Policy, eds. A. Alemmano and S. Gabbi. Ashgate, 2014. http://bit.ly/1k2EwdD.

  • In this paper, Spina “presents some reflections on how the collaborative and crowdsourcing practices of Open Government could be integrated in the activities of EFSA [European Food Safety Authority] and other EU agencies,” with a particular focus on “highlighting the benefits of the Open Government paradigm for expert regulatory bodies in the EU.”
  • Spina argues that the “crowdsourcing of expertise and the reconfiguration of the information flows between European agencies and teh public could represent a concrete possibility of modernising the role of agencies with a new model that has a low financial burden and an almost immediate effect on the legal governance of agencies.”
  • He concludes that, “It is becoming evident that in order to guarantee that the best scientific expertise is provided to EU institutions and citizens, EFSA should strive to use the best organisational models to source science and expertise.”