Exploring the Usefulness of User-Generated Content for Business Intelligence in Innovation

Daradkeh, Mohammad

doi:10.4018/ijeis.2021040103

Cited by 18 publications

(18 citation statements)

References 61 publications

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“…From an online OI community, Daradkeh (2021) presented that information timeless and completeness have a positive effect on the usefulness of user-generated content based on the bug comments collected from Huawei. Accordingly, a suitable OI model plays a key role in the development of companies.…”

Section: The Individual Oi Strategies With the Business Modelmentioning

confidence: 99%

Open Innovation: A Research Framework and Case Study of Huawei

Zhang

et al. 2023

Technological and Economic Development of Economy

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Open innovation (OI) has received significant attention from practices and theories over the past decades. This paper investigates the role of OI and personalized patterns in firms at home and abroad, and then measures the risks involved. Firstly, this paper reviews the definition of OI, the business model innovation characteristics, and the facing problems in practice. Based on the existing literature, we illustrate the openness and challenges of business OI. By introducing bibliometrics, this paper presents a whole research framework. Based on keywords cooccurrence analysis and clustering analysis, we locate the current research hotspots and potential research opportunities from a comprehensive perspective. According to the analysis results, five clusters are obtained, including resource management and value creation; collective innovation and form sustainability; innovation management, intellectual property management, and crossborder cooperation; knowledge management and knowledge sharing; innovation ecosystem, big data, and policy-level innovation. Taking Huawei as an example, its typical business OI model is studied from the perspectives of organizational, project-related, marketing and consumer-based, and summaries the facing challenges and risks. We illustrate its financial performance, innovation performance, and development prospects. We found that, during the implementation of OI practical activities and theoretical exploration, the risks and opportunities facing small and medium-sized enterprises (SMEs) are multiple dimensional.

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Section: The Individual Oi Strategies With the Business Modelmentioning

confidence: 99%

Open Innovation: A Research Framework and Case Study of Huawei

Zhang

et al. 2023

Technological and Economic Development of Economy

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“…The word-by-topic matrix indicates how a group of words can be used to form a topic. Conversely, the topic-by-document matrix reveals how people perceive important topics and in turn can indicate people' sentiment tendencies toward topics (Daradkeh, 2021b). Because the goal of this study is to analyze community sentiment toward COVID-19 vaccine misinformation topics, only relevant sentiment and most relevant COVID-19 vaccine misinformation topics were examined.…”

Section: Modeling and Detection Of Misinformation Topicsmentioning

confidence: 99%

Analyzing Sentiments and Diffusion Characteristics of COVID-19 Vaccine Misinformation Topics in Social Media

Daradkeh

2021

International Journal of Business Analytics

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This study presents a data analytics framework that aims to analyze topics and sentiments associated with COVID-19 vaccine misinformation in social media. A total of 40,359 tweets related to COVID-19 vaccination were collected between January 2021 and March 2021. Misinformation was detected using multiple predictive machine learning models. Latent Dirichlet Allocation (LDA) topic model was used to identify dominant topics in COVID-19 vaccine misinformation. Sentiment orientation of misinformation was analyzed using a lexicon-based approach. An independent-samples t-test was performed to compare the number of replies, retweets, and likes of misinformation with different sentiment orientations. Based on the data sample, the results show that COVID-19 vaccine misinformation included 21 major topics. Across all misinformation topics, the average number of replies, retweets, and likes of tweets with negative sentiment was 2.26, 2.68, and 3.29 times higher, respectively, than those with positive sentiment.

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“…Information usefulness as a topic is addressed in the literature from different perspectives. Generally, most studies discussed information usefulness in the context of business intelligence [12] and more specifically in business internet services [13]. Evaluating information usefulness shared in online communities is a critical issue specially in this area of big data and knowledge sharing in social media.…”

Section: Introductionmentioning

confidence: 99%

“…In his method, the author used a text analytic framework to extract important features from online forums in order to evaluate the information usefulness. In another work, Daradkeh [12] examines the usefulness of user generated content with large amounts of redundant information in order to analyze the digital voice of users in online open innovation communities. Generally, used approaches for information usefulness evaluation are based on extracting many features from online discussions and classify the usefulness of either threads or posts [14].…”

Section: Introductionmentioning

confidence: 99%

“…Generally, used approaches for information usefulness evaluation are based on extracting many features from online discussions and classify the usefulness of either threads or posts [14]. Such features concerns for example relevancy, objectivity, timelessness an completeness of each post [12], [14]. Despite the critical need for evaluating information usefulness in online communities it is noticeable that few studies have tackled this issue.…”

Section: Introductionmentioning

confidence: 99%

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Knowledge graph-based method for solutions detection and evaluation in an online problem-solving community

Sekkal

Amrous²,

Bennani

2022

IJECE

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<span lang="EN-US">Online communities are a real medium for human experiences sharing. They contain rich knowledge of lived situations and experiences that can be used to support decision-making process and problem-solving. This work presents an approach for extracting, representing, and evaluating components of problem-solving knowledge shared in online communities. Few studies have tackled the issue of knowledge extraction and its usefulness evaluation in online communities. In this study, we propose a new approach to detect and evaluate best solutions to problems discussed by members of online communities. Our approach is based on knowledge graph technology and graphs theory enabling the representation of knowledge shared by the community and facilitating its reuse. Our process of problem-solving knowledge extraction in online communities (PSKEOC) consists of three phases: problems and solutions detection and classification, knowledge graph constitution and finally best solutions evaluation. The experimental results are compared to the World Health Organization (WHO) model chapter about Infant and young child feeding and show that our approach succeed to extract and reveal important problem-solving knowledge contained in online community’s conversations. Our proposed approach leads to the construction of an experiential knowledge graph as a representation of the constructed knowledge base in the community studied in this paper.</span>

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Exploring the Usefulness of User-Generated Content for Business Intelligence in Innovation

Cited by 18 publications

References 61 publications

Open Innovation: A Research Framework and Case Study of Huawei

Open Innovation: A Research Framework and Case Study of Huawei

Analyzing Sentiments and Diffusion Characteristics of COVID-19 Vaccine Misinformation Topics in Social Media

Knowledge graph-based method for solutions detection and evaluation in an online problem-solving community

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