MORE THAN THE TONE: THE IMPACT OF SOCIAL MEDIA OPINIONS ON INNOVATION INVESTMENTS
2018
- 172Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage172
- Abstract Views103
- Downloads69
Article Description
Social media is a valuable knowledge source for firm innovation. Extending the literature of both social media and innovation management, we attempt to examine how the valence and volume of user-generated content (UGC) from social media influence firm organizational innovation behav-iours. In this research-in-progress study, we have reviewed the existing literatures and proposed three hypotheses. Firstly, we propose that valence of UGC from social media has a U-shaped rela-tion with firm innovation investments. In particular, compared with neutral UGC, both negative and positive contents are found to push firms to invest more in innovation. Secondly, we argued that such a curvilinear relation is mitigated with an increase in volume of UGC. Last but not least, we argued that firm investment in innovation improves firm performance. To validate our pro-posed hypotheses, we have designed an innovative framework of sentiment analysis and collected a large dataset including 5-year panel with 886 listed firms and their relevant 6.2 million micro-blogs. The preliminary results from applying sentiment analysis into the collected dataset are re-ported in this study. In the future, we will validate our hypotheses with more sophisticated estima-tion models and strict robustness check. The potential contribution to theory and practice is also discussed.
Bibliographic Details
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