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Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 25/09/2018 LAST_PRICE: 0.021781746896101 PX_VOLUME: 22.146 VOLATILITY_10D: 20.65 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.2318181818181818 TEXTBLOB_POLARITY: @intel | Predicted 1_DAY_RETURN: 0.0163363101720758
Predicted 2_DAY_RETURN: 0.0163363101720758
Predicted 7_DAY_RETURN: 23389874.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Just saw this on Amazon: Dick Van Dyke Show Mini Poster #01 11x17 by Unknown for $10.99 https://t.co/H8PYoCrLZm via @amazon" 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: 25/09/2018 DATE: 1974.55 | 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 -0.1 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: 25/09/2018 1_DAY_RETURN: -0.0301537059076751 2_DAY_RETURN: -0.0301537059076751 3_DAY_RETURN: -0.0169658909624977 7_DAY_RETURN: 4538407.0 | 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: 25/09/2018 LAST_PRICE: -0.0203540047099339 PX_VOLUME: 27.407 VOLATILITY_10D: 23.156 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.1 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0301537059076751
Predicted 2_DAY_RETURN: -0.0301537059076751
Predicted 7_DAY_RETURN: 4538407.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @donie: The Facebook account for USA Really is still live. @facebook says it is investigating and was aware of the account before CNN co…" 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: "Facebook" STOCK: 25/09/2018 DATE: 164.91 | 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 0.16818181818181818 and the TextBlob polarity score is @facebook. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 25/09/2018 1_DAY_RETURN: -0.0120065490267417 2_DAY_RETURN: -0.0120065490267417 3_DAY_RETURN: -0.0279546419258988 7_DAY_RETURN: 27622806.0 | 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: 25/09/2018 LAST_PRICE: 0.0030319568249348 PX_VOLUME: 20.871 VOLATILITY_10D: 22.482 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.16818181818181818 TEXTBLOB_POLARITY: @facebook | Predicted 1_DAY_RETURN: -0.0120065490267417
Predicted 2_DAY_RETURN: -0.0120065490267417
Predicted 7_DAY_RETURN: 27622806.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Great event today with @Cisco at the Cisco Connects event in Green Bay WI! Hal Katch doing a great job explaining… https://t.co/PhAgBn8lgu" 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: "Cisco" STOCK: 25/09/2018 DATE: 48.47 | 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 0.275 and the TextBlob polarity score is @Cisco. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 25/09/2018 1_DAY_RETURN: 0.0018568186507118 2_DAY_RETURN: 0.0018568186507118 3_DAY_RETURN: -0.0208376315246543 7_DAY_RETURN: 15810798.0 | 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: 25/09/2018 LAST_PRICE: -0.0006189395502372 PX_VOLUME: 12.027 VOLATILITY_10D: 14.064 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.275 TEXTBLOB_POLARITY: @Cisco | Predicted 1_DAY_RETURN: 0.0018568186507118
Predicted 2_DAY_RETURN: 0.0018568186507118
Predicted 7_DAY_RETURN: 15810798.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @donie: The Facebook account for USA Really is still live. @facebook says it is investigating and was aware of the account before CNN co…" 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: "Facebook" STOCK: 25/09/2018 DATE: 164.91 | 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 0.16818181818181818 and the TextBlob polarity score is @facebook. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 25/09/2018 1_DAY_RETURN: -0.0120065490267417 2_DAY_RETURN: -0.0120065490267417 3_DAY_RETURN: -0.0279546419258988 7_DAY_RETURN: 27622806.0 | 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: 25/09/2018 LAST_PRICE: 0.0030319568249348 PX_VOLUME: 20.871 VOLATILITY_10D: 22.482 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.16818181818181818 TEXTBLOB_POLARITY: @facebook | Predicted 1_DAY_RETURN: -0.0120065490267417
Predicted 2_DAY_RETURN: -0.0120065490267417
Predicted 7_DAY_RETURN: 27622806.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@verizon @VerizonSupport @VZWSupport 2nd time in 3 weeks Verizon has cut service out intentionally in my area, no o… https://t.co/NXSQm3FJ3y
" STOCK: Verizon DATE: 25/09/2018 | 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: Verizon 1_DAY_RETURN: 0.0092365692742695 2_DAY_RETURN: 0.0258246936852027 3_DAY_RETURN: 0.0258246936852027 7_DAY_RETURN: 0.0252591894439208 | 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: Verizon LAST_PRICE: 53.05 PX_VOLUME: 13604924.0 VOLATILITY_10D: 15.28 VOLATILITY_30D: 15.635 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0092365692742695
Predicted 2_DAY_RETURN: 0.0258246936852027
Predicted 7_DAY_RETURN: 0.0252591894439208 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @darrenrovell: JUST IN: @amazon announces that an @HannahStormESPN & Andrea Kremer will be the announcing team for Amazon Prime’s presen…" 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: 25/09/2018 DATE: 1974.55 | 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: 25/09/2018 1_DAY_RETURN: -0.0301537059076751 2_DAY_RETURN: -0.0301537059076751 3_DAY_RETURN: -0.0169658909624977 7_DAY_RETURN: 4538407.0 | 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: 25/09/2018 LAST_PRICE: -0.0203540047099339 PX_VOLUME: 27.407 VOLATILITY_10D: 23.156 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0301537059076751
Predicted 2_DAY_RETURN: -0.0301537059076751
Predicted 7_DAY_RETURN: 4538407.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Lipper_Alpha: Nike Ad Spurs 61% Rise In Sold Out Items - Read more from @JharonneMartis about how the #JustDoIT advert affected @Nike 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: "Nike" STOCK: 25/09/2018 DATE: 84.79 | 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 0.5 and the TextBlob polarity score is @Nike. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 25/09/2018 1_DAY_RETURN: 0.0089633211463614 2_DAY_RETURN: 0.0089633211463614 3_DAY_RETURN: 0.0055431064984078 7_DAY_RETURN: 10519535.0 | 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: 25/09/2018 LAST_PRICE: -0.0061327986790896 PX_VOLUME: 18.387 VOLATILITY_10D: 19.656 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.5 TEXTBLOB_POLARITY: @Nike | Predicted 1_DAY_RETURN: 0.0089633211463614
Predicted 2_DAY_RETURN: 0.0089633211463614
Predicted 7_DAY_RETURN: 10519535.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @bancosantander: Andrea Orcel appointed Santander Group CEO from early 2019. José Antonio Álvarez will be Santander Spain’s new Executiv…" 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: "Santander" STOCK: 25/09/2018 DATE: 4.476 | 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 0.1 and the TextBlob polarity score is @bancosantander. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 25/09/2018 1_DAY_RETURN: 0.0214477211796246 2_DAY_RETURN: 0.0214477211796246 3_DAY_RETURN: -0.0199955317247542 7_DAY_RETURN: 39157071.0 | 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: 25/09/2018 LAST_PRICE: 0.0005585344057194 PX_VOLUME: 19.41 VOLATILITY_10D: 16.498 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.1 TEXTBLOB_POLARITY: @bancosantander | Predicted 1_DAY_RETURN: 0.0214477211796246
Predicted 2_DAY_RETURN: 0.0214477211796246
Predicted 7_DAY_RETURN: 39157071.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @darrenrovell: JUST IN: @amazon announces that an @HannahStormESPN & Andrea Kremer will be the announcing team for Amazon Prime’s presen…" 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: 25/09/2018 DATE: 1974.55 | 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: 25/09/2018 1_DAY_RETURN: -0.0301537059076751 2_DAY_RETURN: -0.0301537059076751 3_DAY_RETURN: -0.0169658909624977 7_DAY_RETURN: 4538407.0 | 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: 25/09/2018 LAST_PRICE: -0.0203540047099339 PX_VOLUME: 27.407 VOLATILITY_10D: 23.156 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0301537059076751
Predicted 2_DAY_RETURN: -0.0301537059076751
Predicted 7_DAY_RETURN: 4538407.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @IakoubiY: Just saw this on Amazon: Haggar Men's Work-To-Weekend No-Iron Pleat-Front... by Haggar https://t.co/16jvqUkZfA via @amazon" 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: 25/09/2018 DATE: 1974.55 | 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: 25/09/2018 1_DAY_RETURN: -0.0301537059076751 2_DAY_RETURN: -0.0301537059076751 3_DAY_RETURN: -0.0169658909624977 7_DAY_RETURN: 4538407.0 | 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: 25/09/2018 LAST_PRICE: -0.0203540047099339 PX_VOLUME: 27.407 VOLATILITY_10D: 23.156 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0301537059076751
Predicted 2_DAY_RETURN: -0.0301537059076751
Predicted 7_DAY_RETURN: 4538407.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @ATT: For just $49.99, get the Samsung Galaxy Express Prime 3! No contract, credit check or activation fee. Hurry, offer ends soon!
" STOCK: Samsung DATE: 25/09/2018 | 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: Samsung 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: 0.0 7_DAY_RETURN: -0.040084388185654 | 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: Samsung LAST_PRICE: 47400.0 PX_VOLUME: 14476906.0 VOLATILITY_10D: 30.334 VOLATILITY_30D: 26.138 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: -0.040084388185654 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@reeses @amazon My thing is to help people on my game site we made a Facebook page you help someone they help you a… https://t.co/20iYOabTzI" 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: "Facebook" STOCK: 25/09/2018 DATE: 164.91 | 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 -0.4 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: 25/09/2018 1_DAY_RETURN: -0.0120065490267417 2_DAY_RETURN: -0.0120065490267417 3_DAY_RETURN: -0.0279546419258988 7_DAY_RETURN: 27622806.0 | 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: 25/09/2018 LAST_PRICE: 0.0030319568249348 PX_VOLUME: 20.871 VOLATILITY_10D: 22.482 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.4 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0120065490267417
Predicted 2_DAY_RETURN: -0.0120065490267417
Predicted 7_DAY_RETURN: 27622806.0 |
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 HP Pavilion - 15t Laptop 2TB HD, 8GB SDRAM, Intel Core i5-7200 Brand New in Box #HP https://t.co/6JdEMHpt0T via @eBay
" STOCK: Intel DATE: 25/09/2018 | 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: Intel 1_DAY_RETURN: 0.021781746896101 2_DAY_RETURN: 0.0163363101720758 3_DAY_RETURN: 0.0163363101720758 7_DAY_RETURN: 0.0041385319102593 | 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: Intel LAST_PRICE: 45.91 PX_VOLUME: 23389874.0 VOLATILITY_10D: 22.146 VOLATILITY_30D: 20.65 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.13636363636363635 | Predicted 1_DAY_RETURN: 0.021781746896101
Predicted 2_DAY_RETURN: 0.0163363101720758
Predicted 7_DAY_RETURN: 0.0041385319102593 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@rocketw49 @Tesla @elonmusk @BMWUSA @BMW your move BMW https://t.co/DNbpmcp7aa" 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: "BMW" STOCK: 25/09/2018 DATE: 78.9 | 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 @BMW. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 25/09/2018 1_DAY_RETURN: 0.0865652724968314 2_DAY_RETURN: 0.0865652724968314 3_DAY_RETURN: 0.0480354879594422 7_DAY_RETURN: 6485172.0 | 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: 25/09/2018 LAST_PRICE: 0.0583016476552597 PX_VOLUME: 39.798 VOLATILITY_10D: 24.731 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @BMW | Predicted 1_DAY_RETURN: 0.0865652724968314
Predicted 2_DAY_RETURN: 0.0865652724968314
Predicted 7_DAY_RETURN: 6485172.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Reuters Oh brother, that is just the tip of the enormous Google Iceberg.
" STOCK: Google DATE: 25/09/2018 | 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: -0.0120027808257043 2_DAY_RETURN: -0.0182345107170679 3_DAY_RETURN: -0.0182345107170679 7_DAY_RETURN: -0.0224308772164941 | 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: Google LAST_PRICE: 1193.89 PX_VOLUME: 1657809.0 VOLATILITY_10D: 18.397 VOLATILITY_30D: 18.381 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0120027808257043
Predicted 2_DAY_RETURN: -0.0182345107170679
Predicted 7_DAY_RETURN: -0.0224308772164941 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @intel: Check out @FastCompany’s coverage on how Smithsonian @AmericanArt Museum and Intel are using #VR to share art with the world." 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: "Intel" STOCK: 25/09/2018 DATE: 45.91 | 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 @intel. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 25/09/2018 1_DAY_RETURN: 0.0163363101720758 2_DAY_RETURN: 0.0163363101720758 3_DAY_RETURN: 0.0041385319102593 7_DAY_RETURN: 23389874.0 | 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: 25/09/2018 LAST_PRICE: 0.021781746896101 PX_VOLUME: 22.146 VOLATILITY_10D: 20.65 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @intel | Predicted 1_DAY_RETURN: 0.0163363101720758
Predicted 2_DAY_RETURN: 0.0163363101720758
Predicted 7_DAY_RETURN: 23389874.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @fanofblues67: @ThePizzaTech @TMobile Verizon is 1000 times better than T Mobile" 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: "Verizon" STOCK: 25/09/2018 DATE: 53.05 | 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 0.5 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: 25/09/2018 1_DAY_RETURN: 0.0258246936852027 2_DAY_RETURN: 0.0258246936852027 3_DAY_RETURN: 0.0252591894439208 7_DAY_RETURN: 13604924.0 | 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: 25/09/2018 LAST_PRICE: 0.0092365692742695 PX_VOLUME: 15.28 VOLATILITY_10D: 15.635 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.5 TEXTBLOB_POLARITY: @TMobile | Predicted 1_DAY_RETURN: 0.0258246936852027
Predicted 2_DAY_RETURN: 0.0258246936852027
Predicted 7_DAY_RETURN: 13604924.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @MitchelmoreMHA: Expedia: St. Anthony among country’s most charming historic towns | Northern Pen https://t.co/jqZNNzHIDm @Expedia @TCII…" 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: "Expedia" STOCK: 25/09/2018 DATE: 130.78 | 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 0.4 and the TextBlob polarity score is @Expedia. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 25/09/2018 1_DAY_RETURN: 0.022556965896926 2_DAY_RETURN: 0.022556965896926 3_DAY_RETURN: -0.0007646429117601 7_DAY_RETURN: 1411343.0 | 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: 25/09/2018 LAST_PRICE: 0.010934393638171 PX_VOLUME: 17.611 VOLATILITY_10D: 21.085 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.4 TEXTBLOB_POLARITY: @Expedia | Predicted 1_DAY_RETURN: 0.022556965896926
Predicted 2_DAY_RETURN: 0.022556965896926
Predicted 7_DAY_RETURN: 1411343.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Disney "We don't condone James Gunn buttttt he does have some good ideas." -Disney 9/2018
" STOCK: Disney DATE: 25/09/2018 | 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 0.7. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Disney 1_DAY_RETURN: -0.0075684238317345 2_DAY_RETURN: -0.0284255918331425 3_DAY_RETURN: -0.0284255918331425 7_DAY_RETURN: -0.0360820205931531 | 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: Disney LAST_PRICE: 113.63 PX_VOLUME: 12169388.0 VOLATILITY_10D: 18.4 VOLATILITY_30D: 12.358 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.7 | Predicted 1_DAY_RETURN: -0.0075684238317345
Predicted 2_DAY_RETURN: -0.0284255918331425
Predicted 7_DAY_RETURN: -0.0360820205931531 |
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