Distributed seeing: Algorithms and the reconfiguration of the workplace, a case of 'automated' trading

2021 | Information and Organization | Citations: 0

Authors: Willems, Thijs; Hafermalz, Ella

Abstract: Contemporary organizations increasingly rely on digital technologies structuring ... Expand

Abstract: Contemporary organizations increasingly rely on digital technologies structuring how work gets done. Algorithms in particular are fundamental for such technologies. Management literature on digital transformation has studied how algorithms either automate or augment work. In doing so, this literature treats algorithms as largely independent from existing work practices. This paper, on the contrary, theorizes and empirically illustrates how algorithms transform the workplace in a spatiotemporal sense by introducing a new epistemic vantage point through which work is un­ derstood. We do so by drawing on previous work on reconfiguration and ‘Ways of Seeing’, and through a qualitative case study on sports trading. Our analysis shows that traders and algorithms each perceive and see the market in specific, though incomplete ways. Since this market is partly virtual and constituted via a range of heterogeneous actors, ‘seeing’ the market entails knowing its distributed nature and pulling spatiotemporal distant elements together. Our paper contributes to the literature on the effects of algorithms on work by putting forward the conceptual lens of ‘distributed seeing’. This highlights that digital transformation is more than an instrumental optimization process by automating or augmenting tasks with technology but that it actively reconfigures the work to be done. We show that digital transformation 1) is reciprocal and thus irreversible; 2) patchworked and thus requires mending work; 3) introduces new organizational vulnerabilities. Collapse

Topics: digital transformation electronic trading big data website human computer interaction

Methods: computational algorithm theory development case study survey qualitative interview

Multi-interest User Profiling in Short Text Microblogs

2020 | DESRIST | Citations: 0

Authors: Wandabwa, Herman; Naeem, M. Asif; Mirza, Farhaan; Pears, Russel; Nguyen, Andy

Abstract: Discourse on short text platforms like Twitter shapes the design of underlying k ... Expand

Abstract: Discourse on short text platforms like Twitter shapes the design of underlying knowledge-based recommendation engines. The resulting recommendations are powered by user connections as social network nodes as well as with shared interests. Twitter as a platform provides a complex mesh of users’ interest levels where some users tend to consume certain topical content to a lesser or greater extent. This consumption of content is usually considered a defining factor in curation of their online identity. Our aim in this paper is to quantify the multi-interests of users based on the tweets they disseminate. We do this by (i) representing all tweets as vectors for computations (ii) generating cluster centroids representative of the topics of interest. (iii) computing a responsibility matrix to depict their interest levels in the topics (iv) aggregating intra-user interest levels to define the user’s multi-topic affinities. We use a Twitter dataset geolocated to Kenya to validate users’ intra-topical interests. Our experimental results demonstrate the effectiveness of our approach in terms of capturing their multi-interests and in turn generate their multi-topic interest profiles. Collapse

Topics: Twitter microblog missing data

Methods: word2vec artificial neural network computational algorithm conceptual modelling support vector machine

Modeling Fixed Odds Betting for Future Event Prediction

2017 | Management Information Systems Quarterly | Citations: 3

Authors: Chen, Weiyun; Li, Xin; Zeng, Daniel

Abstract: Prediction markets provide a promising approach for future event prediction. Mos ... Expand

Abstract: Prediction markets provide a promising approach for future event prediction. Most existing prediction market approaches are based on auction mechanisms. Despite their theoretical appeal and success in various application settings, these mechanisms suffer from several major drawbacks. First, opinions from experts and amateurs are treated equally. Second, continuous attention from participants is assumed. Third, such mechanisms are subject to various forms of market manipulation. To alleviate these limitations, we propose to employ the classic fixed odds betting as an alternative prediction market mechanism. We build a structural model based on a belief–decision framework as the event probability estimator. This belief–decision framework models bettors’ beliefs with mixed beta distributions and bettors’ decisions with prospect theory. A maximum likelihood approach is applied to estimate the model parameters. We conducted experiments on three real-world betting datasets to evaluate our proposed approach. Experimental results show that fixed odds betting based prediction outperforms the reduced form models based on odds and betting results, and achieves a comparable performance with auction-based prediction markets. The results suggest the possibility of employing fixed odds betting as a prediction market in a variety of application contexts where the assumptions made by auction-based approaches do not hold. Collapse

Topics: decision making website privacy information exchange digital news

Methods: experiment descriptive statistic computational algorithm post-hoc analysis Student's t-test

Theories: prospect theory cumulative prospect theory

Minimizing Risk with Users Who Embrace it: Innovative Approaches to Online Gambling

2017 | Americas Conference on Information Systems | Citations: 0

Authors: Hazarika, Bidyut Bikash; Mousavizadeh, Mohammadreza; Rea, Alan; Aghakhani, Navid Aghakhani

Abstract: In recent years online innovations in Internet content offerings has produced a ... Expand

Abstract: In recent years online innovations in Internet content offerings has produced a myriad of highly interactive fantasy sports and gambling sites designed to entice users to wage funds. Although factors such as accessibility and anonymity help motivate people to bet online, many hesitate to wager for reasons that must be examined if online betting websites (OBW) are to continue to innovate and grow. Our research examines how OBW users’ past experiences and perceived reputation influences psychological contract violation (PCV) and perceived institutional effectiveness as they pertain to OBW offerings. We also investigate the effect of institutional effectiveness on users’ concerns and betting behavioral intention. Initial results suggest that OBW users have concerns about transactional information even though they tend to be less risk adverse than non-OBW users. This study also found that psychological contract violation minimizes users’ perception about overall OBW structures’ effectiveness developed to protect online gamblers. Collapse

Topics: online gambling information privacy concern website privacy participatory design

Methods: partial least squares regression design methodology survey archival research

Prediction from regional angst – A study of NFL sentiment in Twitter using technical stock market charting

2017 | Decision Support Systems | Citations: 0

Authors: Schumaker, Robert P.; Labedz, Chester S.; Jarmoszko, A. Tomasz; Brown, Leonard L.

Abstract: To predict NFL game outcomes, we examine the application of technical stock mark ... Expand

Abstract: To predict NFL game outcomes, we examine the application of technical stock market techniques to sentiment gathered from social media. From our analysis we found a $14.84 average return per sentiment-based wager compared to a $12.21 average return loss on the entire 256 games of the 2015–2016 regular season if using an odds-only approach. We further noted that wagers on underdogs (i.e., the less favored teams) that exhibit a “golden cross” pattern in sentiment (e.g., the most recent sentiment signal crosses the longer baseline sentiment), netted a $48.18 return per wager on 41 wagers. These results show promise of cross-domain research and we believe that applying stock market techniques to sports wagering may open an entire new research area. Collapse

Topics: Twitter crowdsourcing social media application programming interface team productivity

Methods: sentiment analysis time series analysis longitudinal research descriptive statistic natural language processing

Social network-embedded prediction markets: The effects of information acquisition and communication on predictions

2013 | Decision Support Systems | Citations: 0

Authors: Qiu, Liangfei; Rui, Huaxia; Whinston, Andrew

Abstract: Information aggregation mechanisms are designed explicitly for collecting and ag ... Expand

Abstract: Information aggregation mechanisms are designed explicitly for collecting and aggregating dispersed information. An excellent example of the use of this “wisdom of crowds” is a prediction market. The purpose of our social network-embedded prediction market is to suggest that carefully designed market mechanisms can elicit and gather dispersed information that can improve our predictions. Simulation results show that our network-embedded prediction market can produce better predictions as a result of the information exchange in social networks and can outperform other non-networked prediction markets. It is shown that forecasting errors decrease with the cost of acquiring information in a network-embedded prediction market. We also develop an information system that combines the power of prediction markets with the popularity of Twitter. Collapse

Topics: social network Twitter information exchange price dispersion smartphone

Methods: simulation survey pilot experiment experiment natural language processing

Theories: game theory

Factors Influencing Intention to Gamble Online

2008 | Americas Conference on Information Systems | Citations: 0

Authors: Lee, Chang Boon Patrick; Xia, Lin Hammer

Abstract: The objective of this research was to validate a model on online gambling intent ... Expand

Abstract: The objective of this research was to validate a model on online gambling intention. Given that there are many forms of online gambling, this research focused on sports betting. We adopted the Technology Acceptance Model (TAM) as our research model. Additionally, we included subjective norm as an antecedent to online gambling intention. We tested the model using data collected from a questionnaire survey. We collected 212 returns from students in a Chinese tertiary institution. The results provide support for the six hypotheses proposed in our research. We discussed the implications of the results for industry practitioners and gambling counselors. Collapse

Topics: online gambling perceived usefulness perceived ease of use website technology adoption

Methods: survey factor analysis data transformation structural equation modeling descriptive statistic

Theories: technology acceptance model

An Empirical Investigation of the Forecast Accuracy of Play-Money Prediction Markets and Professional Betting Markets

2008 | European Conference On Information Systems | Citations: 0

Authors: Slamka, Christian; Luckner, Stefan; Seeman, Thomas; Schroder, Jan

Abstract: Prediction markets have proven high forecasting performance in many areas such a ... Expand

Abstract: Prediction markets have proven high forecasting performance in many areas such as politics, sports and business-related fields compared to traditional instruments such as polls or expert opinions. The advantage of real-money prediction markets is to provide participants with a clear incentive to reveal their true opinion on the outcome of an event. However, it is to date unclear whether play-money prediction markets, where participants cannot suffer any losses, perform well compared to other, more strongly incentivized instruments. Thus, the goal of this paper is to compare the forecast accuracy of play-money prediction markets with that of instruments with a monetary incentive to make as accurate predictions as possible, namely fixed-odds betting. We present the results of an empirical study that compares the forecast accuracy of a play-money prediction market for the FIFA World Cup 2006 to predictions derived from odds issued by two professional betting companies. Additionally, we compare the prediction market with two more benchmarks, namely the FIFA world ranking which is based on historic data and a random predictor. We find that the play-money prediction markets for the FIFA World Cup are about as accurate as betting markets. Moreover, the prediction markets clearly outperform the FIFA world ranking as well as the random predictions. Collapse

Topics: electronic trading

Methods: descriptive statistic literature study