Investor sentiment networks: mapping connectedness in DJIA stocks
Abstract This study examines the connectedness of firm-level online investor sentiment using Dow Jones Industrial Average constituent stocks. Leveraging two proxies of online textual sentiment, namely news media and social media sentiment, we investigate sentiment connectedness at two levels: freque...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-01-01
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| Series: | Financial Innovation |
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| Online Access: | https://doi.org/10.1186/s40854-024-00675-7 |
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| author | Kingstone Nyakurukwa Yudhvir Seetharam |
| author_facet | Kingstone Nyakurukwa Yudhvir Seetharam |
| author_sort | Kingstone Nyakurukwa |
| collection | DOAJ |
| description | Abstract This study examines the connectedness of firm-level online investor sentiment using Dow Jones Industrial Average constituent stocks. Leveraging two proxies of online textual sentiment, namely news media and social media sentiment, we investigate sentiment connectedness at two levels: frequency interval and asymmetric level. Frequency connectedness dissects connectedness into short-, medium-, and long-term investing horizons, while asymmetric connectedness focuses on the transmission of positive and negative sentiment shocks on news and social media platforms. Our results reveal interesting patterns in which both news and social media sentiments demonstrate consistency in connectedness across the short-, medium-, and long-term. Regarding asymmetric connectedness, we observe that negative news sentiment has a higher connectedness than positive news sentiments. |
| format | Article |
| id | doaj-art-47faee30f258437fb188b8ff3fe515f6 |
| institution | Kabale University |
| issn | 2199-4730 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Financial Innovation |
| spelling | doaj-art-47faee30f258437fb188b8ff3fe515f62025-01-05T12:43:44ZengSpringerOpenFinancial Innovation2199-47302025-01-0111111910.1186/s40854-024-00675-7Investor sentiment networks: mapping connectedness in DJIA stocksKingstone Nyakurukwa0Yudhvir Seetharam1University of the WitwatersrandUniversity of the WitwatersrandAbstract This study examines the connectedness of firm-level online investor sentiment using Dow Jones Industrial Average constituent stocks. Leveraging two proxies of online textual sentiment, namely news media and social media sentiment, we investigate sentiment connectedness at two levels: frequency interval and asymmetric level. Frequency connectedness dissects connectedness into short-, medium-, and long-term investing horizons, while asymmetric connectedness focuses on the transmission of positive and negative sentiment shocks on news and social media platforms. Our results reveal interesting patterns in which both news and social media sentiments demonstrate consistency in connectedness across the short-, medium-, and long-term. Regarding asymmetric connectedness, we observe that negative news sentiment has a higher connectedness than positive news sentiments.https://doi.org/10.1186/s40854-024-00675-7Behavioral financeSentiment contagionSocial media sentimentNews media sentiment |
| spellingShingle | Kingstone Nyakurukwa Yudhvir Seetharam Investor sentiment networks: mapping connectedness in DJIA stocks Financial Innovation Behavioral finance Sentiment contagion Social media sentiment News media sentiment |
| title | Investor sentiment networks: mapping connectedness in DJIA stocks |
| title_full | Investor sentiment networks: mapping connectedness in DJIA stocks |
| title_fullStr | Investor sentiment networks: mapping connectedness in DJIA stocks |
| title_full_unstemmed | Investor sentiment networks: mapping connectedness in DJIA stocks |
| title_short | Investor sentiment networks: mapping connectedness in DJIA stocks |
| title_sort | investor sentiment networks mapping connectedness in djia stocks |
| topic | Behavioral finance Sentiment contagion Social media sentiment News media sentiment |
| url | https://doi.org/10.1186/s40854-024-00675-7 |
| work_keys_str_mv | AT kingstonenyakurukwa investorsentimentnetworksmappingconnectednessindjiastocks AT yudhvirseetharam investorsentimentnetworksmappingconnectednessindjiastocks |