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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: 23/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0165938641094768 3_DAY_RETURN: 0.0049994881070198 7_DAY_RETURN: 4561119.0 | 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: 23/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 20.526 VOLATILITY_10D: 17.930999999999994 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.025 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0165938641094768
Predicted 7_DAY_RETURN: 4561119.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "I wish @Apple update for the Apple Watch fix the delete recent app by completely removing the recent apps by swipin… https://t.co/3zOdZNUNFD" 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: 24/09/2018 DATE: 220.79 | 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 0.03333333333333333 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: 24/09/2018 1_DAY_RETURN: -0.0141763666832736 2_DAY_RETURN: -0.0141763666832736 3_DAY_RETURN: -0.0131799447438742 7_DAY_RETURN: 27693358.0 | 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: 24/09/2018 LAST_PRICE: -0.0141763666832736 PX_VOLUME: 25.142 VOLATILITY_10D: 20.148 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.03333333333333333 TEXTBLOB_POLARITY: @Apple | Predicted 1_DAY_RETURN: -0.0141763666832736
Predicted 2_DAY_RETURN: -0.0141763666832736
Predicted 7_DAY_RETURN: 27693358.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @J_PopCultureFan: 🌟🌟🌟 VOTE SAM FOR AFH! 🌟🌟🌟
🔴 CBS Website: https://t.co/mM5klWbkna
🔴 CBS Messenger Bot: @CBS - Send a message to acti…
" STOCK: CBS DATE: 24/09/2018 | 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: CBS 1_DAY_RETURN: 0.0028278543655002 2_DAY_RETURN: 0.0028278543655002 3_DAY_RETURN: 0.0028278543655002 7_DAY_RETURN: -0.0053022269353127 | 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: CBS LAST_PRICE: 56.58 PX_VOLUME: 3679314.0 VOLATILITY_10D: 15.781 VOLATILITY_30D: 18.07 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0028278543655002
Predicted 2_DAY_RETURN: 0.0028278543655002
Predicted 7_DAY_RETURN: -0.0053022269353127 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Apple: Drop by Lincoln Park or Wicker Park September 21–23 to get exclusive offers when you use Apple Pay. It’s easy and secure." 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: 24/09/2018 DATE: 220.79 | 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 0.1 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: 24/09/2018 1_DAY_RETURN: -0.0141763666832736 2_DAY_RETURN: -0.0141763666832736 3_DAY_RETURN: -0.0131799447438742 7_DAY_RETURN: 27693358.0 | 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: 24/09/2018 LAST_PRICE: -0.0141763666832736 PX_VOLUME: 25.142 VOLATILITY_10D: 20.148 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.1 TEXTBLOB_POLARITY: @Apple | Predicted 1_DAY_RETURN: -0.0141763666832736
Predicted 2_DAY_RETURN: -0.0141763666832736
Predicted 7_DAY_RETURN: 27693358.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@PayPal bans Infowars? Who needs PayPal..... I dont. Will never use them as long as they supress speech." 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: "PayPal" STOCK: 24/09/2018 DATE: 89.62 | 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 @PayPal. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 24/09/2018 1_DAY_RETURN: 0.0111582236108011 2_DAY_RETURN: 0.0111582236108011 3_DAY_RETURN: -0.010488730194153 7_DAY_RETURN: 8303272.0 | 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: 24/09/2018 LAST_PRICE: 0.0111582236108011 PX_VOLUME: 20.894 VOLATILITY_10D: 24.389 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @PayPal | Predicted 1_DAY_RETURN: 0.0111582236108011
Predicted 2_DAY_RETURN: 0.0111582236108011
Predicted 7_DAY_RETURN: 8303272.0 |
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 this Amazon deal: Emotional Intelligence 2.0 by Travis Bradberry https://t.co/0Z1vTj0Fal 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: 24/09/2018 DATE: 1934.36 | 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: 24/09/2018 1_DAY_RETURN: -0.0100033085878533 2_DAY_RETURN: -0.0100033085878533 3_DAY_RETURN: -0.0136117372154097 7_DAY_RETURN: 4213728.0 | 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: 24/09/2018 LAST_PRICE: -0.0100033085878533 PX_VOLUME: 24.298 VOLATILITY_10D: 22.63300000000001 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0100033085878533
Predicted 2_DAY_RETURN: -0.0100033085878533
Predicted 7_DAY_RETURN: 4213728.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@TMobile @JohnLegere @WellsAdams @BrandiCyrus Party with eBay money? Instead of this b.... why you don’t try to fix… https://t.co/d2ZlT1aOmE" 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: "eBay" STOCK: 24/09/2018 DATE: 33.72 | 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 @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: 24/09/2018 1_DAY_RETURN: 0.0094899169632265 2_DAY_RETURN: 0.0094899169632265 3_DAY_RETURN: 0.0142348754448399 7_DAY_RETURN: 8746536.0 | 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: 24/09/2018 LAST_PRICE: 0.0094899169632265 PX_VOLUME: 9.487 VOLATILITY_10D: 14.181 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @TMobile | Predicted 1_DAY_RETURN: 0.0094899169632265
Predicted 2_DAY_RETURN: 0.0094899169632265
Predicted 7_DAY_RETURN: 8746536.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Next on #bbcgms business news - it’s been a tough few months on the high street . Now online retailer @eBay is laun… https://t.co/AEHpUvB0ew" 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: 24/09/2018 DATE: 5124.0 | 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 -0.10722222222222222 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: 24/09/2018 1_DAY_RETURN: 0.0148321623731459 2_DAY_RETURN: 0.0148321623731459 3_DAY_RETURN: 0.04839968774395 7_DAY_RETURN: 676500.0 | 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: 24/09/2018 LAST_PRICE: 0.0148321623731459 PX_VOLUME: 18.666 VOLATILITY_10D: 15.32 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.10722222222222222 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.0148321623731459
Predicted 2_DAY_RETURN: 0.0148321623731459
Predicted 7_DAY_RETURN: 676500.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@rial_rocks @PayPal @Forbes Add PayPal to the list of corporations engaged in Racketeering against conservative voi… https://t.co/GrRTcn5grp" 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: "PayPal" STOCK: 24/09/2018 DATE: 89.62 | 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 @PayPal. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 24/09/2018 1_DAY_RETURN: 0.0111582236108011 2_DAY_RETURN: 0.0111582236108011 3_DAY_RETURN: -0.010488730194153 7_DAY_RETURN: 8303272.0 | 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: 24/09/2018 LAST_PRICE: 0.0111582236108011 PX_VOLUME: 20.894 VOLATILITY_10D: 24.389 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @PayPal | Predicted 1_DAY_RETURN: 0.0111582236108011
Predicted 2_DAY_RETURN: 0.0111582236108011
Predicted 7_DAY_RETURN: 8303272.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@amazon I have been dealing with Amazon for a book purchase for about a month and I am very disappointed in their c… https://t.co/9dTFDCEJBp" 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: 24/09/2018 DATE: 1934.36 | 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 -0.975 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: 24/09/2018 1_DAY_RETURN: -0.0100033085878533 2_DAY_RETURN: -0.0100033085878533 3_DAY_RETURN: -0.0136117372154097 7_DAY_RETURN: 4213728.0 | 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: 24/09/2018 LAST_PRICE: -0.0100033085878533 PX_VOLUME: 24.298 VOLATILITY_10D: 22.63300000000001 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.975 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0100033085878533
Predicted 2_DAY_RETURN: -0.0100033085878533
Predicted 7_DAY_RETURN: 4213728.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Verizon to create next-generation global network infrastructure for @SAP #IamVZ https://t.co/xUGJpPXWN6 https://t.co/0wvjyORcMS" 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: 24/09/2018 DATE: 53.54 | 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: 24/09/2018 1_DAY_RETURN: 0.0164363093014569 2_DAY_RETURN: 0.0164363093014569 3_DAY_RETURN: 0.0216660440791932 7_DAY_RETURN: 14029601.0 | 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: 24/09/2018 LAST_PRICE: 0.0164363093014569 PX_VOLUME: 15.532 VOLATILITY_10D: 15.775 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP | Predicted 1_DAY_RETURN: 0.0164363093014569
Predicted 2_DAY_RETURN: 0.0164363093014569
Predicted 7_DAY_RETURN: 14029601.0 |
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: Advanced Graphics Life Size Cardboard Cutout Sta... by Advanced Graphics https://t.co/bb0gjsD6nb 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: 24/09/2018 DATE: 1934.36 | 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: 24/09/2018 1_DAY_RETURN: -0.0100033085878533 2_DAY_RETURN: -0.0100033085878533 3_DAY_RETURN: -0.0136117372154097 7_DAY_RETURN: 4213728.0 | 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: 24/09/2018 LAST_PRICE: -0.0100033085878533 PX_VOLUME: 24.298 VOLATILITY_10D: 22.63300000000001 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.4 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0100033085878533
Predicted 2_DAY_RETURN: -0.0100033085878533
Predicted 7_DAY_RETURN: 4213728.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Microsoft: Starting soon: Microsoft CEO @SatyaNadella will kick off #MSIgnite. Tune in here: https://t.co/kVe49uxS8n" 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: "Microsoft" STOCK: 24/09/2018 DATE: 114.67 | 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 @Microsoft. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 24/09/2018 1_DAY_RETURN: -0.0035754774570506 2_DAY_RETURN: -0.0035754774570506 3_DAY_RETURN: -0.0220633121130199 7_DAY_RETURN: 27334460.0 | 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: 24/09/2018 LAST_PRICE: -0.0035754774570506 PX_VOLUME: 15.723 VOLATILITY_10D: 17.349 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Microsoft | Predicted 1_DAY_RETURN: -0.0035754774570506
Predicted 2_DAY_RETURN: -0.0035754774570506
Predicted 7_DAY_RETURN: 27334460.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Homegate with Lipton® Iced Tea from Walmart this NFL season. @Walmart #LiptonHomegating #Sponsored… https://t.co/n7JaQ9mlYy" 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: "Walmart" STOCK: 24/09/2018 DATE: 94.92 | 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: 24/09/2018 1_DAY_RETURN: 0.0103244837758112 2_DAY_RETURN: 0.0103244837758112 3_DAY_RETURN: -0.0010535187526338 7_DAY_RETURN: 5336981.0 | 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: 24/09/2018 LAST_PRICE: 0.0103244837758112 PX_VOLUME: 10.044 VOLATILITY_10D: 29.862 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Walmart | Predicted 1_DAY_RETURN: 0.0103244837758112
Predicted 2_DAY_RETURN: 0.0103244837758112
Predicted 7_DAY_RETURN: 5336981.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "BMW presents the future with the piloted electric vision iNext @BMW https://t.co/q0bI5o2rac" 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: 24/09/2018 DATE: 83.5 | 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: 24/09/2018 1_DAY_RETURN: 0.0267065868263473 2_DAY_RETURN: 0.0267065868263473 3_DAY_RETURN: -0.015688622754491 7_DAY_RETURN: 2313312.0 | 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: 24/09/2018 LAST_PRICE: 0.0267065868263473 PX_VOLUME: 23.057 VOLATILITY_10D: 18.445 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @BMW | Predicted 1_DAY_RETURN: 0.0267065868263473
Predicted 2_DAY_RETURN: 0.0267065868263473
Predicted 7_DAY_RETURN: 2313312.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Microsoft Microsoft
💥◯◯ starts now 💥
Thank you very much.
#Microsoft #MSIgnite
" STOCK: Microsoft DATE: 24/09/2018 | 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 0.26. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Microsoft 1_DAY_RETURN: -0.0035754774570506 2_DAY_RETURN: -0.0035754774570506 3_DAY_RETURN: -0.0035754774570506 7_DAY_RETURN: -0.0220633121130199 | 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: Microsoft LAST_PRICE: 114.67 PX_VOLUME: 27334460.0 VOLATILITY_10D: 15.723 VOLATILITY_30D: 17.349 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.26 | Predicted 1_DAY_RETURN: -0.0035754774570506
Predicted 2_DAY_RETURN: -0.0035754774570506
Predicted 7_DAY_RETURN: -0.0220633121130199 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Starbucks customer service is slipping in the last two weeks at 3 different locations. Next time I'm dropping locations and names. Fed up." 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: 24/09/2018 DATE: 5124.0 | 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 -0.03333333333333333 and the TextBlob polarity score is @Starbucks. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 24/09/2018 1_DAY_RETURN: 0.0148321623731459 2_DAY_RETURN: 0.0148321623731459 3_DAY_RETURN: 0.04839968774395 7_DAY_RETURN: 676500.0 | 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: 24/09/2018 LAST_PRICE: 0.0148321623731459 PX_VOLUME: 18.666 VOLATILITY_10D: 15.32 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.03333333333333333 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: 0.0148321623731459
Predicted 2_DAY_RETURN: 0.0148321623731459
Predicted 7_DAY_RETURN: 676500.0 |
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 2014 Nike LeBron XI 11 Grafitti White Red Black Wolf Cool Grey 616175-100 NEW 14 #Nike https://t.co/7pW43mSXF5 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: "Nike" STOCK: 24/09/2018 DATE: 84.27 | 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 0.04494949494949494 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: 24/09/2018 1_DAY_RETURN: 0.015189272576243 2_DAY_RETURN: 0.015189272576243 3_DAY_RETURN: -0.0119852853921916 7_DAY_RETURN: 8770355.0 | 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: 24/09/2018 LAST_PRICE: 0.015189272576243 PX_VOLUME: 18.296 VOLATILITY_10D: 19.621 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.04494949494949494 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.015189272576243
Predicted 2_DAY_RETURN: 0.015189272576243
Predicted 7_DAY_RETURN: 8770355.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Ryanair Hi Ryanair could someone please tell me if I could put an umbrella into the hold as “infant luggage” if no… https://t.co/mf1wMr5ZQl" 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. |
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