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Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Reuters 1_DAY_RETURN: 0.0030856971334234 2_DAY_RETURN: 0.0006603631997598 3_DAY_RETURN: 0.0055090299664815 7_DAY_RETURN: 0.0033058182000101 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Reuters LAST_PRICE: 49.9725 PX_VOLUME: 3027903.0 VOLATILITY_10D: 10.397 VOLATILITY_30D: 13.679 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: -0.05 | Predicted 1_DAY_RETURN: 0.0030856971334234
Predicted 2_DAY_RETURN: 0.0006603631997598
Predicted 7_DAY_RETURN: 0.0033058182000101 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Ford F-Max named International Truck of the Year 2019! MAN and PSA were also up in the running. @Ford #truck… https://t.co/hjDkbU8aUH" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Ford" STOCK: 21/09/2018 DATE: 9.85 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Ford. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: -0.0071065989847716 2_DAY_RETURN: -0.0274111675126903 3_DAY_RETURN: -0.0406091370558376 7_DAY_RETURN: 74488637.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: -0.0040609137055836 PX_VOLUME: 12.186 VOLATILITY_10D: 22.242 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Ford | Predicted 1_DAY_RETURN: -0.0071065989847716
Predicted 2_DAY_RETURN: -0.0274111675126903
Predicted 7_DAY_RETURN: 74488637.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Audi: Alexa, electric has gone Audi.
The fully electric e-tron is here with in-car Alexa integration. https://t.co/GD1nab0M1A
" STOCK: Audi DATE: 21/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Audi 1_DAY_RETURN: -0.0130548302872062 2_DAY_RETURN: -0.0287206266318537 3_DAY_RETURN: -0.0339425587467362 7_DAY_RETURN: -0.0469973890339425 | The stock shows a consistent negative return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Audi LAST_PRICE: 766.0 PX_VOLUME: 56.0 VOLATILITY_10D: 28.68 VOLATILITY_30D: 24.137 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0130548302872062
Predicted 2_DAY_RETURN: -0.0287206266318537
Predicted 7_DAY_RETURN: -0.0469973890339425 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "SAP S/4HANA 1809 is officially released! @SAP #S4HANA #SAP https://t.co/kQuZxWc4V8" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "SAP" STOCK: 21/09/2018 DATE: 103.72 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @SAP. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: -0.0121480910142692 2_DAY_RETURN: -0.0067489394523717 3_DAY_RETURN: 0.0052063247204011 7_DAY_RETURN: 7439837.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: -0.0177400694176629 PX_VOLUME: 17.451 VOLATILITY_10D: 17.397000000000002 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP | Predicted 1_DAY_RETURN: -0.0121480910142692
Predicted 2_DAY_RETURN: -0.0067489394523717
Predicted 7_DAY_RETURN: 7439837.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Just bought a few more @CaptureShow (Mark Seliger) books off of @amazon yesterday. Next round will include… https://t.co/0eMqf7c9ny" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Next" STOCK: 21/09/2018 DATE: 5200.0 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.15 and the TextBlob polarity score is @amazon. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: 0.0126923076923076 2_DAY_RETURN: 0.0269230769230769 3_DAY_RETURN: 0.0288461538461538 7_DAY_RETURN: 1032536.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: 0.0234615384615384 PX_VOLUME: 18.597 VOLATILITY_10D: 15.567 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.15 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: 0.0126923076923076
Predicted 2_DAY_RETURN: 0.0269230769230769
Predicted 7_DAY_RETURN: 1032536.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "You know @FedEx is hopping today with all the new @Apple iPhone XS, iPhone XS Max, and Apple Watch Series 4 being d… https://t.co/IvXIpsJU19
" STOCK: Apple DATE: 21/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.13636363636363635. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Apple 1_DAY_RETURN: 0.0108885417623817 2_DAY_RETURN: 0.0032619682072958 3_DAY_RETURN: 0.0026647064228614 7_DAY_RETURN: 0.0283929063677295 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Apple LAST_PRICE: 217.66 PX_VOLUME: 96246748.0 VOLATILITY_10D: 27.839 VOLATILITY_30D: 19.836 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.13636363636363635 | Predicted 1_DAY_RETURN: 0.0108885417623817
Predicted 2_DAY_RETURN: 0.0032619682072958
Predicted 7_DAY_RETURN: 0.0283929063677295 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @ForeverLogical: Check out this Amazon deal: Fear: Trump in the White House by Bob Woodward https://t.co/IXyjEr4WRu via @amazon https://…" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Amazon" STOCK: 21/09/2018 DATE: 1915.01 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @amazon. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: 0.0059581934297993 2_DAY_RETURN: 0.0135978402201554 3_DAY_RETURN: 0.0288144709427105 7_DAY_RETURN: 6855898.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: 0.0152949592952517 PX_VOLUME: 27.813 VOLATILITY_10D: 22.493 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: 0.0059581934297993
Predicted 2_DAY_RETURN: 0.0135978402201554
Predicted 7_DAY_RETURN: 6855898.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "So many eBay treats arriving daily for babygirls party. Exciting, love an ebay day #party #onlyoneonce @eBay
" STOCK: eBay DATE: 21/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.25. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: eBay 1_DAY_RETURN: 0.0058754406580494 2_DAY_RETURN: 0.0052878965922444 3_DAY_RETURN: 0.0023501762632196 7_DAY_RETURN: 0.0017626321974148 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: eBay LAST_PRICE: 34.04 PX_VOLUME: 24874963.0 VOLATILITY_10D: 10.372 VOLATILITY_30D: 14.015 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.25 | Predicted 1_DAY_RETURN: 0.0058754406580494
Predicted 2_DAY_RETURN: 0.0052878965922444
Predicted 7_DAY_RETURN: 0.0017626321974148 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @cvanellaa: She’s literally a princess that Disney needs to cast @Disney just saying. https://t.co/vc7PG268tt" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Disney" STOCK: 21/09/2018 DATE: 110.4 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Disney. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: -0.0055253623188405 2_DAY_RETURN: -0.0078804347826087 3_DAY_RETURN: -0.0103260869565217 7_DAY_RETURN: 25753718.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: 0.0110507246376811 PX_VOLUME: 15.975 VOLATILITY_10D: 10.466 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Disney | Predicted 1_DAY_RETURN: -0.0055253623188405
Predicted 2_DAY_RETURN: -0.0078804347826087
Predicted 7_DAY_RETURN: 25753718.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Check out Touch Screen LCD Retina Display Frame for Apple iPhone 4 Black Screen Glass New https://t.co/n785JLN6dO via @eBay" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Apple" STOCK: 21/09/2018 DATE: 217.66 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.015151515151515154 and the TextBlob polarity score is @eBay. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: 0.0032619682072958 2_DAY_RETURN: 0.0026647064228614 3_DAY_RETURN: 0.0283929063677295 7_DAY_RETURN: 96246748.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: 0.0108885417623817 PX_VOLUME: 27.839 VOLATILITY_10D: 19.836 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.015151515151515154 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.0032619682072958
Predicted 2_DAY_RETURN: 0.0026647064228614
Predicted 7_DAY_RETURN: 96246748.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @SpelmanPres: Apple HBCU Scholars Adesuwa H. Joseph, C'2019, and Kelsie Warmack, C'2019, interned @Apple this summer, learning about the…
" STOCK: Apple DATE: 21/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Apple 1_DAY_RETURN: 0.0108885417623817 2_DAY_RETURN: 0.0032619682072958 3_DAY_RETURN: 0.0026647064228614 7_DAY_RETURN: 0.0283929063677295 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Apple LAST_PRICE: 217.66 PX_VOLUME: 96246748.0 VOLATILITY_10D: 27.839 VOLATILITY_30D: 19.836 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0108885417623817
Predicted 2_DAY_RETURN: 0.0032619682072958
Predicted 7_DAY_RETURN: 0.0283929063677295 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@TMobile does UPS not ship on Saturday's??" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "UPS" STOCK: 21/09/2018 DATE: 118.49 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @TMobile. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: -0.0020254873829014 2_DAY_RETURN: -0.0021098826905224 3_DAY_RETURN: 0.0160351084479703 7_DAY_RETURN: 4348507.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: 0.0053169043801165 PX_VOLUME: 18.144 VOLATILITY_10D: 14.879 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @TMobile | Predicted 1_DAY_RETURN: -0.0020254873829014
Predicted 2_DAY_RETURN: -0.0021098826905224
Predicted 7_DAY_RETURN: 4348507.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Wow! I am planning to switch from Dell to HP now
@HP @HPIndia #keepreinventing
" STOCK: HP DATE: 21/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.125. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: HP 1_DAY_RETURN: -0.0054200542005418 2_DAY_RETURN: -0.022067363530778 3_DAY_RETURN: -0.0259388308168795 7_DAY_RETURN: -0.0305845915602012 | The stock shows a consistent negative return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: HP LAST_PRICE: 25.83 PX_VOLUME: 21915838.0 VOLATILITY_10D: 11.559 VOLATILITY_30D: 15.026 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.125 | Predicted 1_DAY_RETURN: -0.0054200542005418
Predicted 2_DAY_RETURN: -0.022067363530778
Predicted 7_DAY_RETURN: -0.0305845915602012 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Next day delivery my ass @Apple! Ordered my phone Wednesday and now it won't be here until Monday." STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Next" STOCK: 21/09/2018 DATE: 5200.0 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Apple. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: 0.0126923076923076 2_DAY_RETURN: 0.0269230769230769 3_DAY_RETURN: 0.0288461538461538 7_DAY_RETURN: 1032536.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: 0.0234615384615384 PX_VOLUME: 18.597 VOLATILITY_10D: 15.567 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Apple | Predicted 1_DAY_RETURN: 0.0126923076923076
Predicted 2_DAY_RETURN: 0.0269230769230769
Predicted 7_DAY_RETURN: 1032536.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@IvankaTrump @POTUS @Walmart What do you think of you dad attacking Dr. Ford" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Ford" STOCK: 21/09/2018 DATE: 9.85 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Walmart. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: -0.0071065989847716 2_DAY_RETURN: -0.0274111675126903 3_DAY_RETURN: -0.0406091370558376 7_DAY_RETURN: 74488637.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: -0.0040609137055836 PX_VOLUME: 12.186 VOLATILITY_10D: 22.242 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Walmart | Predicted 1_DAY_RETURN: -0.0071065989847716
Predicted 2_DAY_RETURN: -0.0274111675126903
Predicted 7_DAY_RETURN: 74488637.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@rachelroyalkc @Apple This is an actual thing. Had a friend that worked for Apple share that with me." STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Apple" STOCK: 21/09/2018 DATE: 217.66 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Apple. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: 0.0032619682072958 2_DAY_RETURN: 0.0026647064228614 3_DAY_RETURN: 0.0283929063677295 7_DAY_RETURN: 96246748.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: 0.0108885417623817 PX_VOLUME: 27.839 VOLATILITY_10D: 19.836 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Apple | Predicted 1_DAY_RETURN: 0.0032619682072958
Predicted 2_DAY_RETURN: 0.0026647064228614
Predicted 7_DAY_RETURN: 96246748.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@HarvardBiz Google Pixel Fraud might happen again with the launch of Pixel 3 on 9 October 2018
@Google is Killing.… https://t.co/lRCuOWauVw
" STOCK: Google DATE: 21/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Google 1_DAY_RETURN: 0.0165938641094768 2_DAY_RETURN: 0.0018342831791967 3_DAY_RETURN: -0.0042743063850117 7_DAY_RETURN: 0.0049994881070198 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Google LAST_PRICE: 1172.12 PX_VOLUME: 4561119.0 VOLATILITY_10D: 20.526 VOLATILITY_30D: 17.930999999999994 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0165938641094768
Predicted 2_DAY_RETURN: 0.0018342831791967
Predicted 7_DAY_RETURN: 0.0049994881070198 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@TruthFinderJ832 @OriginalFunko @amazon It's Ana (Overwatch character) and it's an Amazon exclusive. (Left is commo… https://t.co/qFALOb5Rm5" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Amazon" STOCK: 21/09/2018 DATE: 1915.01 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @amazon. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: 0.0059581934297993 2_DAY_RETURN: 0.0135978402201554 3_DAY_RETURN: 0.0288144709427105 7_DAY_RETURN: 6855898.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: 0.0152949592952517 PX_VOLUME: 27.813 VOLATILITY_10D: 22.493 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: 0.0059581934297993
Predicted 2_DAY_RETURN: 0.0135978402201554
Predicted 7_DAY_RETURN: 6855898.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@IvankaTrump @POTUS @Walmart Will you be standing up for women and Dr. Ford? Doubtful. You keep validating what a… https://t.co/CMDGstVAWM" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Ford" STOCK: 21/09/2018 DATE: 9.85 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Walmart. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: -0.0071065989847716 2_DAY_RETURN: -0.0274111675126903 3_DAY_RETURN: -0.0406091370558376 7_DAY_RETURN: 74488637.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: -0.0040609137055836 PX_VOLUME: 12.186 VOLATILITY_10D: 22.242 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Walmart | Predicted 1_DAY_RETURN: -0.0071065989847716
Predicted 2_DAY_RETURN: -0.0274111675126903
Predicted 7_DAY_RETURN: 74488637.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Check out 1977 Porsche Turbo Carrera Sports Car Compare Audi Fox Sedan Photo Print Ad #Porsche https://t.co/FMYFGR0VKT via @eBay" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Audi" STOCK: 21/09/2018 DATE: 766.0 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @eBay. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 21/09/2018 1_DAY_RETURN: -0.0287206266318537 2_DAY_RETURN: -0.0339425587467362 3_DAY_RETURN: -0.0469973890339425 7_DAY_RETURN: 56.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 21/09/2018 LAST_PRICE: -0.0130548302872062 PX_VOLUME: 28.68 VOLATILITY_10D: 24.137 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0287206266318537
Predicted 2_DAY_RETURN: -0.0339425587467362
Predicted 7_DAY_RETURN: 56.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "T-Mobile starts to detail in-home 5G goals, plans to take on Charter and Comcast! Yes yes yes! @TMobile @JohnLegere… https://t.co/8KxfUUkKfW
" STOCK: Comcast DATE: 21/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Comcast 1_DAY_RETURN: -0.0023746701846964 2_DAY_RETURN: -0.0153034300791556 3_DAY_RETURN: -0.0042216358839049 7_DAY_RETURN: -0.0248021108179418 | The stock shows a consistent negative return trend over the specified periods. |
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