instruction
stringclasses 3
values | input
stringlengths 33
307
| output
stringlengths 66
248
|
|---|---|---|
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: 31/01/2017 DATE: 31.83 | 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: 31/01/2017 1_DAY_RETURN: 0.021363493559535 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: -0.0578071002199183 7_DAY_RETURN: 9469076.0 | 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: 31/01/2017 LAST_PRICE: 0.0106817467797676 PX_VOLUME: 33.029 VOLATILITY_10D: 22.932 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.021363493559535
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: 9469076.0 |
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 Book in Russian - "Prayer for deliverance from illnesses" Prayer Shield Religion https://t.co/zaDhDI6Hxt via @eBay
" STOCK: eBay DATE: 31/01/2017 | 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: eBay 1_DAY_RETURN: 0.0106817467797676 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: 0.021363493559535 7_DAY_RETURN: -0.0578071002199183 | 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: eBay LAST_PRICE: 31.83 PX_VOLUME: 9469076.0 VOLATILITY_10D: 33.029 VOLATILITY_30D: 22.932 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0106817467797676
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: -0.0578071002199183 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @DrJimmyStar: Check out gx by Gwen Stefani Hadda Purse NWT https://t.co/xcVahsLOyk @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: "eBay" STOCK: 31/01/2017 DATE: 31.83 | 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: 31/01/2017 1_DAY_RETURN: 0.021363493559535 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: -0.0578071002199183 7_DAY_RETURN: 9469076.0 | 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: 31/01/2017 LAST_PRICE: 0.0106817467797676 PX_VOLUME: 33.029 VOLATILITY_10D: 22.932 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.021363493559535
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: 9469076.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @AngelSt35124353: @Starbucks HATE'S AMERICIAN'S!!!!!!! https://t.co/xVohj9fL0i" 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: "Starbucks" STOCK: 31/01/2017 DATE: 55.22 | 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 -1.0 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: 31/01/2017 1_DAY_RETURN: 0.0162984425932632 2_DAY_RETURN: 0.0162984425932632 3_DAY_RETURN: 0.0583122057225642 7_DAY_RETURN: 14307985.0 | 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: 31/01/2017 LAST_PRICE: 0.0123143788482433 PX_VOLUME: 23.916 VOLATILITY_10D: 17.298 VOLATILITY_30D: -1.0 LSTM_POLARITY: -1.0 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: 0.0162984425932632
Predicted 2_DAY_RETURN: 0.0162984425932632
Predicted 7_DAY_RETURN: 14307985.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@HP want to throw laptop in the bin" 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: "HP" STOCK: 31/01/2017 DATE: 15.05 | 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 0.0 and the TextBlob polarity score is @HP. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: -0.0166112956810631 2_DAY_RETURN: -0.0166112956810631 3_DAY_RETURN: 0.0079734219269102 7_DAY_RETURN: 14889607.0 | 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: 31/01/2017 LAST_PRICE: -0.013953488372093 PX_VOLUME: 27.84800000000001 VOLATILITY_10D: 19.862 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @HP | Predicted 1_DAY_RETURN: -0.0166112956810631
Predicted 2_DAY_RETURN: -0.0166112956810631
Predicted 7_DAY_RETURN: 14889607.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @BroadlandPolice: Well done SCs Grint & Kaliski of @NorfolkSpecials who detained a thief with £166 worth of DVDs @Tesco Blue Boar Lan… " 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: "Tesco" STOCK: 31/01/2017 DATE: 194.6 | 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 @Tesco. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0614080164439877 2_DAY_RETURN: 0.0614080164439877 3_DAY_RETURN: -0.0125899280575539 7_DAY_RETURN: 79257504.0 | 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: 31/01/2017 LAST_PRICE: 0.0164439876670093 PX_VOLUME: 60.469 VOLATILITY_10D: 39.887 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.15 TEXTBLOB_POLARITY: @Tesco | Predicted 1_DAY_RETURN: 0.0614080164439877
Predicted 2_DAY_RETURN: 0.0614080164439877
Predicted 7_DAY_RETURN: 79257504.0 |
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 Cadbury Chocolate Christmas Stocking Assorted Selection (208 Grams, Pack of 8) https://t.co/4qopTLvwWS @eBay
" STOCK: eBay DATE: 31/01/2017 | 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 0.5. |
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: 0.0106817467797676 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: 0.021363493559535 7_DAY_RETURN: -0.0578071002199183 | 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: eBay LAST_PRICE: 31.83 PX_VOLUME: 9469076.0 VOLATILITY_10D: 33.029 VOLATILITY_30D: 22.932 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.5 | Predicted 1_DAY_RETURN: 0.0106817467797676
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: -0.0578071002199183 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Lrihendry: CALL @Starbucks 1-800-782-7282 and VENT! Let them know how you feel about them hiring 10K #refugees instead of Amer… " 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: "Starbucks" STOCK: 31/01/2017 DATE: 55.22 | 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 @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: 31/01/2017 1_DAY_RETURN: 0.0162984425932632 2_DAY_RETURN: 0.0162984425932632 3_DAY_RETURN: 0.0583122057225642 7_DAY_RETURN: 14307985.0 | 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: 31/01/2017 LAST_PRICE: 0.0123143788482433 PX_VOLUME: 23.916 VOLATILITY_10D: 17.298 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: 0.0162984425932632
Predicted 2_DAY_RETURN: 0.0162984425932632
Predicted 7_DAY_RETURN: 14307985.0 |
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 Adidas Extreme Power (1x anti-perspirant - 150 ml + 2x deo body spray - 150 ml) #adidas https://t.co/xAIgAO3HtP 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: "eBay" STOCK: 31/01/2017 DATE: 31.83 | 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 -0.125 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: 31/01/2017 1_DAY_RETURN: 0.021363493559535 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: -0.0578071002199183 7_DAY_RETURN: 9469076.0 | 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: 31/01/2017 LAST_PRICE: 0.0106817467797676 PX_VOLUME: 33.029 VOLATILITY_10D: 22.932 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.125 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.021363493559535
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: 9469076.0 |
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 Crystal Quartz Gemstone Shaker Pendant 925 Sterling Silver Diamond Pave Jewelry https://t.co/9ja9aQcQbT 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: "eBay" STOCK: 31/01/2017 DATE: 31.83 | 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: 31/01/2017 1_DAY_RETURN: 0.021363493559535 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: -0.0578071002199183 7_DAY_RETURN: 9469076.0 | 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: 31/01/2017 LAST_PRICE: 0.0106817467797676 PX_VOLUME: 33.029 VOLATILITY_10D: 22.932 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.021363493559535
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: 9469076.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Reuters: BREAKING: Amazon CEO Jeff Bezos says the company is working on more legal options to challenge Trump travel ban" 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: "Reuters" STOCK: 31/01/2017 DATE: 49.3887 | 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 0.35 and the TextBlob polarity score is @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0031221716708478 2_DAY_RETURN: 0.0031221716708478 3_DAY_RETURN: 0.0044605344947324 7_DAY_RETURN: 547029.0 | 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: 31/01/2017 LAST_PRICE: -0.0026767256477695 PX_VOLUME: 9.665 VOLATILITY_10D: 9.094 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.35 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0031221716708478
Predicted 2_DAY_RETURN: 0.0031221716708478
Predicted 7_DAY_RETURN: 547029.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @agnitioMCM: Berfin Demirbilek taking us through digital transformation - coordination and integration are key @Bayer #pharmaconf 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: "Bayer" STOCK: 31/01/2017 DATE: 101.104 | 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 @Bayer. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0318780661497073 2_DAY_RETURN: 0.0318780661497073 3_DAY_RETURN: -0.0127096850767526 7_DAY_RETURN: 2891744.0 | 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: 31/01/2017 LAST_PRICE: 0.0168242601677481 PX_VOLUME: 24.074 VOLATILITY_10D: 16.851 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Bayer | Predicted 1_DAY_RETURN: 0.0318780661497073
Predicted 2_DAY_RETURN: 0.0318780661497073
Predicted 7_DAY_RETURN: 2891744.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Fed likely to keep rates steady as it awaits Trump economic plan https://t.co/R9U7vsavA9 via @Reuters" 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: "Reuters" STOCK: 31/01/2017 DATE: 49.3887 | 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 0.12222222222222225 and the TextBlob polarity score is @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0031221716708478 2_DAY_RETURN: 0.0031221716708478 3_DAY_RETURN: 0.0044605344947324 7_DAY_RETURN: 547029.0 | 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: 31/01/2017 LAST_PRICE: -0.0026767256477695 PX_VOLUME: 9.665 VOLATILITY_10D: 9.094 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.12222222222222225 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0031221716708478
Predicted 2_DAY_RETURN: 0.0031221716708478
Predicted 7_DAY_RETURN: 547029.0 |
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 2 pcs Adidas Action 3 Pro Invisible - antiperspirant spray - 150 ml #adidas https://t.co/kPmdGfAFh9 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: "eBay" STOCK: 31/01/2017 DATE: 31.83 | 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 @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: 31/01/2017 1_DAY_RETURN: 0.021363493559535 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: -0.0578071002199183 7_DAY_RETURN: 9469076.0 | 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: 31/01/2017 LAST_PRICE: 0.0106817467797676 PX_VOLUME: 33.029 VOLATILITY_10D: 22.932 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.1 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.021363493559535
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: 9469076.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@eBay @rohit07688 ebay is horrible, don't bother. Use https://t.co/ypUBCoLqsW
" STOCK: eBay DATE: 31/01/2017 | 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 -1.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: eBay 1_DAY_RETURN: 0.0106817467797676 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: 0.021363493559535 7_DAY_RETURN: -0.0578071002199183 | 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: eBay LAST_PRICE: 31.83 PX_VOLUME: 9469076.0 VOLATILITY_10D: 33.029 VOLATILITY_30D: 22.932 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: -1.0 | Predicted 1_DAY_RETURN: 0.0106817467797676
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: -0.0578071002199183 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Reuters: Some leading French Socialists threaten to desert hard-left Hamon https://t.co/QD1ByteDru https://t.co/ngyosfjrbR" 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: "Reuters" STOCK: 31/01/2017 DATE: 49.3887 | 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 @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0031221716708478 2_DAY_RETURN: 0.0031221716708478 3_DAY_RETURN: 0.0044605344947324 7_DAY_RETURN: 547029.0 | 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: 31/01/2017 LAST_PRICE: -0.0026767256477695 PX_VOLUME: 9.665 VOLATILITY_10D: 9.094 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0031221716708478
Predicted 2_DAY_RETURN: 0.0031221716708478
Predicted 7_DAY_RETURN: 547029.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Liz Clairborne Square Scarf - EUC #LizClairborne https://t.co/Qk2qCfJOix 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: "eBay" STOCK: 31/01/2017 DATE: 31.83 | 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: 31/01/2017 1_DAY_RETURN: 0.021363493559535 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: -0.0578071002199183 7_DAY_RETURN: 9469076.0 | 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: 31/01/2017 LAST_PRICE: 0.0106817467797676 PX_VOLUME: 33.029 VOLATILITY_10D: 22.932 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.021363493559535
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: 9469076.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Custom William Shakespeare Book Page Bracelet https://t.co/NveN50Zdpo via @amazon #asmg #booklover https://t.co/GtFxV6mKDZ" 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: 31/01/2017 DATE: 823.48 | 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: 31/01/2017 1_DAY_RETURN: 0.0149244668965851 2_DAY_RETURN: 0.0149244668965851 3_DAY_RETURN: -0.0012629329188322 7_DAY_RETURN: 3137196.0 | 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: 31/01/2017 LAST_PRICE: 0.0083790741730217 PX_VOLUME: 13.447 VOLATILITY_10D: 16.992 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: 0.0149244668965851
Predicted 2_DAY_RETURN: 0.0149244668965851
Predicted 7_DAY_RETURN: 3137196.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@loadsofvans @amazon oh yessssssssss" 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: 31/01/2017 DATE: 823.48 | 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. |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.