Stakeholder Analyses of Firm-Related Web Forums

Zimbra, David; Chen, Hsinchun

doi:10.1145/2675693

Cited by 14 publications

(3 citation statements)

References 105 publications

(127 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sentiment analysis can be used to systematically quantify subjective information from a patient’s post. We use the Chinese sentiment polarity dictionary, National Taiwan University Semantic Dictionary (NTUSD), developed by Taiwan University, to identify the sentiment of each post p ij of patient i as a negative, neutral, or positive emotion (equation 2, Figure 2 ) [ 25 ], where the sentiment score senti ( p ij ) is the j th post p ij by patient i , length ( p ij ) is the text length of the j th post p ij by patient i,s is number of sentences in the j th post p ij by patient i , and t is sentiment expression terms in sentences, pos ( t,s ) is part of t in sentence s , pol ( t,s ) polarity of t in sentence s , and ntusd(t, pos(t,s), pol(t,s)) is the NTUSD intensity value for term t based on its sentence part pos ( t,s ) and polarity pol ( t,s ). The media literacy of patient i (ie, IL 2 i ) could be calculated as the average sentiment of each post (equation 3, Figure 2 ), assuming the total number of posts by patient i is n during a certain time interval.…”

Section: Methodsmentioning

confidence: 99%

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication

Wu¹

2018

J Med Internet Res

View full text Add to dashboard Cite

BackgroundIn practice, online health communities have passed the adoption stage and reached the diffusion phase of development. In this phase, patients equipped with knowledge regarding the issues involved in health care are capable of switching between different communities to maximize their online health community activities. Online health communities employ doctors to answer patient questions, and high quality online health communities are more likely to be acknowledged by patients. Therefore, the factors that motivate patients to maintain ongoing relationships with online health communities must be addressed. However, this has received limited scholarly attention.ObjectiveThe purpose of this study was to identify the factors that drive patients to continue their use of online health communities where doctor-patient communication occurs. This was achieved by integrating the information system success model with online health community features.MethodsA Web spider was used to download and extract data from one of the most authoritative Chinese online health communities in which communication occurs between doctors and patients. The time span analyzed in this study was from January 2017 to March 2017. A sample of 469 valid anonymous patients with 9667 posts was obtained (the equivalent of 469 respondents in survey research). A combination of Web mining and structural equation modeling was then conducted to test the research hypotheses.ResultsThe results show that the research framework for integrating the information system success model and online health community features contributes to our understanding of the factors that drive patients' relationships with online health communities. The primary findings are as follows: (1) perceived usefulness is found to be significantly determined by three exogenous variables (ie, social support, information quality, and service quality; R2=0.88). These variables explain 87.6% of the variance in perceived usefulness of online health communities; (2) similarly, patient satisfaction was found to be significantly determined by the three variables listed above (R2=0.69). These variables explain 69.3% of the variance seen in patient satisfaction; (3) continuance use (dependent variable) is significantly influenced by perceived usefulness and patient satisfaction (R2=0.93). That is, the combined effects of perceived usefulness and patient satisfaction explain 93.4% of the variance seen in continuance use; and (4) unexpectedly, individual literacy had no influence on perceived usefulness and satisfaction of patients using online health communities.ConclusionsFirst, this study contributes to the existing literature on the continuance use of online health communities using an empirical approach. Second, an appropriate metric was developed to assess constructs related to the proposed research model. Additionally, a Web spider enabled us to acquire objective data relatively easily and frequently, thereby overcoming a major limitation of survey techniques.

show abstract

Section: Methodsmentioning

confidence: 99%

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication

Wu¹

2018

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…The former represents information that is objectively necessary for a trading decision, while the latter denotes what is subjectively considered to be relevant (cf. Zimbra, Chen, & Lusch, 2015). With further advances in text mining, one might be able to analyze information demand (i.e., what is sought by investors in decision making) and extract the relevant parts of disclosures.…”

Section: Discussionmentioning

confidence: 99%

Investor Reaction to Financial Disclosures across Topics: An Application of Latent Dirichlet Allocation*

Feuerriegel

Pröllochs

2018

Decision Sciences

View full text Add to dashboard Cite

This paper provides a holistic study of how stock prices vary in their response to financial disclosures across different topics. Thereby, we specifically shed light into the extensive amount of filings for which no a priori categorization of their content exists. For this purpose, we utilize an approach from data mining -namely, latent Dirichlet allocation -as a means of topic modeling. This technique facilitates our task of automatically categorizing, ex ante, the content of more than 70,000 regulatory 8-K filings from U.S. companies. We then evaluate the subsequent stock market reaction. Our empirical evidence suggests a considerable discrepancy among various types of news stories in terms of their relevance and impact on financial markets. For instance, we find a statistically significant abnormal return in response to earnings results and credit rating, but also for disclosures regarding business strategy, the health sector, as well as mergers and acquisitions. Our results yield findings that benefit managers, investors and policy-makers by indicating how 1 arXiv:1805.03308v1 [cs.CL] 8 May 2018 regulatory filings should be structured and the topics most likely to precede changes in stock valuations.

show abstract

“…Sentiment analysis can be used to systematically quantify subjective information from a patient's post. We use the Chinese sentiment polarity dictionary, National Taiwan University Semantic Dictionary (NTUSD), developed by Taiwan University, to identify the sentiment of each post p ij of patient i as a negative, neutral, or positive emotion (equation 2, Figure 2) [25], where the sentiment score senti(p ij ) is the j th post p ij by patient i, length(p ij ) is the text length of the j th post p ij by patient i,s is number of sentences in the j th post p ij by patient i, and t is sentiment expression terms in sentences, pos(t,s) is part of t in sentence s, pol(t,s) polarity of t in sentence s, and ntusd(t, pos(t,s), pol(t,s)) is the NTUSD intensity value for term t based on its sentence part pos(t,s) and polarity pol(t,s). The media literacy of patient i (ie, IL2 i ) could be calculated as the average sentiment of each post (equation 3, Figure 2), assuming the total number of posts by patient i is n during a certain time interval.…”

Section: Media Literacymentioning

confidence: 99%

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication (Preprint)

Wu¹

2017

Preprint

View full text Add to dashboard Cite

BACKGROUND In practice, online health communities have passed the adoption stage and reached the diffusion phase of development. In this phase, patients equipped with knowledge regarding the issues involved in health care are capable of switching between different communities to maximize their online health community activities. Online health communities employ doctors to answer patient questions, and high quality online health communities are more likely to be acknowledged by patients. Therefore, the factors that motivate patients to maintain ongoing relationships with online health communities must be addressed. However, this has received limited scholarly attention. OBJECTIVE The purpose of this study was to identify the factors that drive patients to continue their use of online health communities where doctor-patient communication occurs. This was achieved by integrating the information system success model with online health community features. METHODS A Web spider was used to download and extract data from one of the most authoritative Chinese online health communities in which communication occurs between doctors and patients. The time span analyzed in this study was from January 2017 to March 2017. A sample of 469 valid anonymous patients with 9667 posts was obtained (the equivalent of 469 respondents in survey research). A combination of Web mining and structural equation modeling was then conducted to test the research hypotheses. RESULTS The results show that the research framework for integrating the information system success model and online health community features contributes to our understanding of the factors that drive patients' relationships with online health communities. The primary findings are as follows: (1) perceived usefulness is found to be significantly determined by three exogenous variables (ie, social support, information quality, and service quality; R2=0.88). These variables explain 87.6% of the variance in perceived usefulness of online health communities; (2) similarly, patient satisfaction was found to be significantly determined by the three variables listed above (R2=0.69). These variables explain 69.3% of the variance seen in patient satisfaction; (3) continuance use (dependent variable) is significantly influenced by perceived usefulness and patient satisfaction (R2=0.93). That is, the combined effects of perceived usefulness and patient satisfaction explain 93.4% of the variance seen in continuance use; and (4) unexpectedly, individual literacy had no influence on perceived usefulness and satisfaction of patients using online health communities. CONCLUSIONS First, this study contributes to the existing literature on the continuance use of online health communities using an empirical approach. Second, an appropriate metric was developed to assess constructs related to the proposed research model. Additionally, a Web spider enabled us to acquire objective data relatively easily and frequently, thereby overcoming a major limitation of survey techniques.

show abstract

Stakeholder Analyses of Firm-Related Web Forums

Cited by 14 publications

References 105 publications

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication

Investor Reaction to Financial Disclosures across Topics: An Application of Latent Dirichlet Allocation*

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication (Preprint)

Contact Info

Product

Resources

About