Laboratory Forensics for Open Science Readiness: an Investigative Approach to Research Data Management

2023 | Information Systems Frontiers | Citations: 0

Authors: Lefebvre, Armel; Spruit, Marco

Abstract: Recently, the topic of research data management has appeared at the forefront of ... Expand

Abstract: Recently, the topic of research data management has appeared at the forefront of Open Science as a prerequisite for preserving and disseminating research data efficiently. At the same time, scientific laboratories still rely upon digital files that are processed by experimenters to analyze and communicate laboratory results. In this study, we first apply a forensic process to investigate the information quality of digital evidence underlying published results. Furthermore, we use semiotics to describe the quality of information recovered from storage systems with laboratory forensics techniques. Next, we formulate laboratory analytics capabilities based on the results of the forensics analysis. Laboratory forensics and analytics form the basis of research data management. Finally, we propose a conceptual overview of open science readiness, which combines laboratory forensics techniques and laboratory analytics capabilities to help overcome research data management challenges in the near future. Collapse

Topics: data management data quality digital forensics digital dashboard digital transformation

Methods: experiment digital trace data case study design artifact exploratory data analysis

Theories: semiotic theory theory of information information systems theory

Managers’ Responses to Online Reviews for Improving Firm Performance: A Text Analytics Approach

2021 | Communications of the Association for Information Systems | Citations: 0

Authors: Deng, Tianjie; Lee, Young-Jin; Xie, Karen

Abstract: ... Expand

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Topics: online review organizational productivity financial performance social media missing data

Methods: natural language processing sentiment analysis product review cluster analysis link analysis

Theories: social exchange theory affect theory

Dynamic, Multidimensional, and Skillset-Specific Reputation Systems for Online Work

2021 | Information Systems Research | Citations: 0

Authors: Kokkodis, Marios

Abstract: Reputation systems in digital workplaces increase transaction efficiency by buil ... Expand

Abstract: Reputation systems in digital workplaces increase transaction efficiency by building trust and reducing information asymmetry. These systems, however, do not yet capture the dynamic multidimensional nature of online work. By uniformly aggregating reputation scores across worker skills, they ignore skillset-specific heterogeneity (reputation attribution), and they implicitly assume that a worker’s quality does not change over time (reputation staticity). Even further, reputation scores tend to be overly positive (reputation inflation), and, as a result, they often fail to differentiate workers efficiently. This work presents a new augmented intelligence reputation framework that combines human input with machine learning to provide dynamic, multidimensional, and skillset-specific worker reputation. The framework includes three components: The first component maps skillsets into a latent space of finite competency dimensions (word embedding), and, as a result, it directly addresses reputation attribution. The second builds dynamic competency-specific quality assessment models (hidden Markov models) that solve reputation staticity. The final component aggregates these competency-specific assessments to generate skillset-specific reputation scores. Application of this framework on a data set of 58,459 completed tasks from a major online labor market shows that, compared to alternative reputation systems, the proposed approach (1) yields more appropriate rankings of workers that form a closer-to-normal reputation distribution, (2) better identifies “nonperfect” workers who are more likely to underperform and are harder to predict, and (3) improves the ranking of within-opening choices and yields significantly better outcomes. Additional analysis of 77,044 restaurant reviews shows that the proposed framework successfully generalizes to alternative contexts, where assigned feedback scores are overly positive and service quality is multidimensional and dynamic. Collapse

Topics: online reputation system recommender system word of mouth online labor market individual productivity

Methods: machine learning descriptive statistic computational algorithm XGBoost word embedding

Preference enhanced hybrid expertise retrieval system in community question answering services

2020 | Decision Support Systems | Citations: 1

Authors: Kundu, Dipankar; Pal, Rajat Kumar; Mandal, Deba Prasad

Abstract: Here, we propose a preference enhanced hybrid expertise retrieval (PEHER) system ... Expand

Abstract: Here, we propose a preference enhanced hybrid expertise retrieval (PEHER) system in community question answering services. PEHER consists of three segments, namely, preferability estimator, authority estimator, and expertise estimator. The preferability estimator utilizes the textual information to determine both intra-profile and inter-profile preferences of answerers for each term. The intra-profile preferences consider the preference of a term using the answering history of a given answerer. The inter-profile preferences incorporate the preferences of all answerers for a term. These preferences are then used to determine the preferability of each answerer for each of the archived questions. The authority estimator considers the textual familiarity between each archived question and the profile of each answerer as the weight of the associated link in the network. The expertise estimator is composed of three blocks, namely, question similarity finder, proficiency estimator, and expert list generator. The question similarity finder finds the similarities between the new question and each of the archived questions. The proficiency estimator uses the said similarities of the archived questions along with their preferabilities to decide the proficiencies of answerers for the new question. Finally, the expert list generator considers the authorities and proficiencies to generate a list of experts for a given question. We compare PEHER with twenty existing methods on four real-world datasets using five performance measures. We find that PEHER outperforms the comparing algorithms in 92.00% (368 out of 400) cases. Collapse

Topics: decision support system Java IT investment

Methods: computational algorithm experiment parametric test Student's t-test question answering

An Explorative Study on the Virtual World: Investigating the Avatar Gender and Avatar Age Differences in their Social Interactions for Help-Seeking

2020 | Information Systems Frontiers | Citations: 0

Authors: Zhang, Yulei Gavin; Dang, Mandy Yan; Chen, Hsinchun

Abstract: This study investigates avatars’ gender and age differences in their help-seekin ... Expand

Abstract: This study investigates avatars’ gender and age differences in their help-seeking interactions in virtual worlds. Specifically, we conducted data collections from two popular help-supporting regions from Second Life, and performed two levels of analyses. We first examined the existence of the overall gender and age differences, and then compared and tested the detailed differences by creating three types of interaction networks based on avatar gender and avatar age, respectively. Overall, we found that the interaction networks of the same gender tended to be more centralized than the interaction networks with mixed genders. In addition, the interaction networks of the same age group tended to be more centralized than the interaction networks with mixed ages. We also found that old-aged avatars had significantly higher values than young-aged avatars in all measurement dimensions, indicating that old-aged avatars played more important roles in help-seeking interactions. Collapse

Topics: Second Life virtual world social identity Java open source

Methods: parametric test laboratory experiment ANOVA descriptive statistic survey

Theories: role theory

Green IT Practices across Industries: A Text-Mining based Analysis

2017 | Americas Conference on Information Systems | Citations: 0

Authors: Deng, Qi; Ji, Shaobo; Wang, Yun

Abstract: In this paper, we employ a practical perspective and examine the Green IT (GIT) ... Expand

Abstract: In this paper, we employ a practical perspective and examine the Green IT (GIT) practices across industries using a dictionary-based text mining method. Our research includes two phases: 1) building a GIT dictionary for text mining, and 2) examining GIT practices proliferation in non-IT industries. As the first attempt of using dictionary-based text mining method to study the Green IT practices, this paper has two main implications. First, through building the Green IT dictionary, we provide a broad view of current Green IT practices and present a tool that can be used to examine Green IT practices in future research. Second, while employing a practical perspective, this paper identifies some research gaps which could be addressed in future GIT research. Collapse

Topics: green IS remote work IT supported collaboration video conference IS sourcing

Methods: natural language processing link analysis hierarchical clustering literature study

Political Social Media Sites as Public Sphere: A Case Study of the Norwegian Labour Party

2014 | Communications of the Association for Information Systems | Citations: 1

Authors: Rohde Johannessen, Marius; Følstad, Asbjørn

Abstract: Political interest and voter turnout is in steady decline. In an attempt to ren ... Expand

Abstract: Political interest and voter turnout is in steady decline. In an attempt to renew interest for political matters, political parties and governments have attempted to create new digital meeting places, with the hope that social media can contribute to renew the public sphere and thereby increase political awareness in the population. Communicating in new media demands adaption to the culture of the new medium, and the networked nature of the Internet poses challenges to old ways of thinking as we can no longer talk about one public sphere but rather a networked public sphere consisting of a multitude of discussion spaces. In this article, we contribute to the understanding of the networked public sphere and online political communication through a case study of MyLaborParty.no, a social network run by a Norwegian political party. Our findings indicate that political parties can create a thriving part of the networked public sphere, as long as they invite opposing voices to the discussion, communicate using the genres which facilitate discussion and have users or moderators who help spread ideas between discussion spaces. Collapse

Topics: website social media site social media network effect spreadsheet

Methods: network analysis case study qualitative interview qualitative content analysis link analysis

Recommendation as link prediction in bipartite graphs: A graph kernel-based machine learning approach

2013 | Decision Support Systems | Citations: 0

Authors: Li, Xin; Chen, Hsinchun

Abstract: Recommender systems have been widely adopted in online applications to suggest p ... Expand

Abstract: Recommender systems have been widely adopted in online applications to suggest products, services, and contents to potential users. Collaborative filtering (CF) is a successful recommendation paradigm that employs transaction information to enrich user and item features for recommendation. By mapping transactions to a bipartite user–item interaction graph, a recommendation problem is converted into a link prediction problem, where the graph structure captures subtle information on relations between users and items. To take advantage of the structure of this graph, we propose a kernel-based recommendation approach and design a novel graph kernel that inspects customers and items (indirectly) related to the focal user–item pair as its context to predict whether there may be a link. In the graph kernel, we generate random walk paths starting from a focal user–item pair and define similarities between user–item pairs based on the random walk paths. We prove the validity of the kernel and apply it in a one-class classification framework for recommendation. We evaluate the proposed approach with three real-world datasets. Our proposed method outperforms state-of-the-art benchmark algorithms, particularly when recommending a large number of items. The experiments show the necessity of capturing user–item graph structure in recommendation. Collapse

Topics: recommender system decision support system

Methods: computational algorithm experiment machine learning support vector machine link analysis

Who is Retweeting the Tweeters? Modeling, Originating, and Promoting Behaviors in the Twitter Network

2012 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Achananuparp, Palakorn; Lim, Ee-Peng; Jiang, Jing; Hoang, Tuan-Anh

Abstract: Real-time microblogging systems such as Twitter offer users an easy and lightwei ... Expand

Abstract: Real-time microblogging systems such as Twitter offer users an easy and lightweight means to exchange information. Instead of writing formal and lengthy messages, microbloggers prefer to frequently broadcast several short messages to be read by other users. Only when messages are interesting, are they propagated further by the readers. In this article, we examine user behavior relevant to information propagation through microblogging. We specifically use retweeting activities among Twitter users to define and model originating and promoting behavior. We propose a basic model for measuring the two behaviors, a mutual dependency model, which considers the mutual relationships between the two behaviors, and a range-based model, which considers the depth and reach of users’ original tweets. Next, we compare the three behavior models and contrast them with the existing work on modeling influential Twitter users. Last, to demonstrate their applicability, we further employ the behavior models to detect interesting events from sudden changes in aggregated information propagation behavior of Twitter users. The results will show that the proposed behavior models can be effectively applied to detect interesting events in the Twitter stream, compared to the baseline tweet-based approaches. Collapse

Topics: Twitter user behavior electronic mail email spam spamming

Methods: computational algorithm longitudinal research time series analysis experiment descriptive statistic

Constructing a reliable Web graph with information on browsing behavior

2012 | Decision Support Systems | Citations: 0

Authors: Liu, Yiqun; Xue, Yufei; Xu, Danqing; Cen, Rongwei; Zhang, Min; Ma, Shaoping; Ru, Liyun

Abstract: Page quality estimation is one of the greatest challenges for Web search engines ... Expand

Abstract: Page quality estimation is one of the greatest challenges for Web search engines. Hyperlink analysis algorithms such as PageRank and TrustRank are usually adopted for this task. However, low quality, unreliable and even spam data in the Web hyperlink graph makes it increasingly difficult to estimate page quality effectively. Analyzing large-scale user browsing behavior logs, we found that a more reliable Web graph can be constructed by incorporating browsing behavior information. The experimental results show that hyperlink graphs constructed with the proposed methods are much smaller in size than the original graph. In addition, algorithms based on the proposed “surfing with prior knowledge” model obtain better estimation results with these graphs for both high quality page and spam page identification tasks. Hyperlink graphs constructed with the proposed methods evaluate Web page quality more precisely and with less computational effort. Collapse

Topics: email spam search engine web application web page website

Methods: computational algorithm machine learning link analysis digital trace data experiment