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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: 19/09/2018 DATE: 1926.42 | 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 -0.2 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: 19/09/2018 1_DAY_RETURN: -0.0095462048774411 2_DAY_RETURN: 0.022720901983991 3_DAY_RETURN: 0.0330042254544699 7_DAY_RETURN: 4056822.0 | 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: 19/09/2018 LAST_PRICE: 0.0075943978986928 PX_VOLUME: 26.16800000000001 VOLATILITY_10D: 21.99 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.2 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0095462048774411
Predicted 2_DAY_RETURN: 0.022720901983991
Predicted 7_DAY_RETURN: 4056822.0 |
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 Nike The Overplay VIII Men's Basketball Shoes 8 Color Orange Gray & Dark Gray VG #Nike https://t.co/VN4QU7cLRK 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: 19/09/2018 DATE: 84.43 | 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 @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: 19/09/2018 1_DAY_RETURN: -0.0138576335425796 2_DAY_RETURN: -0.0111334833589957 3_DAY_RETURN: -0.0169371076631529 7_DAY_RETURN: 8053129.0 | 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: 19/09/2018 LAST_PRICE: 0.0098306289233684 PX_VOLUME: 17.913 VOLATILITY_10D: 19.231 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.15 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0138576335425796
Predicted 2_DAY_RETURN: -0.0111334833589957
Predicted 7_DAY_RETURN: 8053129.0 |
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: PlayStation VR - Doom Bundle by Sony for $274.99 https://t.co/3WICK9yOCf 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: 19/09/2018 DATE: 1926.42 | 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: 19/09/2018 1_DAY_RETURN: -0.0095462048774411 2_DAY_RETURN: 0.022720901983991 3_DAY_RETURN: 0.0330042254544699 7_DAY_RETURN: 4056822.0 | 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: 19/09/2018 LAST_PRICE: 0.0075943978986928 PX_VOLUME: 26.16800000000001 VOLATILITY_10D: 21.99 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0095462048774411
Predicted 2_DAY_RETURN: 0.022720901983991
Predicted 7_DAY_RETURN: 4056822.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@pucch007 @pepsi I live for Pepsi" 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: "Pepsi" STOCK: 19/09/2018 DATE: 113.77 | 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 0.13636363636363635 and the TextBlob polarity score is @pepsi. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 19/09/2018 1_DAY_RETURN: 0.0143271512701064 2_DAY_RETURN: 0.0070317306847147 3_DAY_RETURN: 0.0007031730684714 7_DAY_RETURN: 2844869.0 | 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: 19/09/2018 LAST_PRICE: 0.0018458293047376 PX_VOLUME: 12.029000000000002 VOLATILITY_10D: 11.901 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.13636363636363635 TEXTBLOB_POLARITY: @pepsi | Predicted 1_DAY_RETURN: 0.0143271512701064
Predicted 2_DAY_RETURN: 0.0070317306847147
Predicted 7_DAY_RETURN: 2844869.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@netflix shares up 5 percent after solid Emmys performance
Netflix shares closed about 5 percent higher Tuesday af… https://t.co/TmKX9R3a4D
" STOCK: Netflix DATE: 19/09/2018 | 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 0.05. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Netflix 1_DAY_RETURN: 0.0018803139306736 2_DAY_RETURN: -0.0452637889688248 3_DAY_RETURN: -0.0065402223675604 7_DAY_RETURN: 0.0081480270329191 | 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: Netflix LAST_PRICE: 366.96 PX_VOLUME: 11876841.0 VOLATILITY_10D: 42.851000000000006 VOLATILITY_30D: 41.694 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.05 | Predicted 1_DAY_RETURN: 0.0018803139306736
Predicted 2_DAY_RETURN: -0.0452637889688248
Predicted 7_DAY_RETURN: 0.0081480270329191 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Nestle, Unilever, Coke make bids in US$4 billion-plus GSK India sale: Sources
#Horlicks @GSK
#Nestle #Unilever… https://t.co/oqGJvg8XiU
" STOCK: Nestle DATE: 19/09/2018 | 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: Nestle 1_DAY_RETURN: 0.00225 2_DAY_RETURN: 0.0099999999999999 3_DAY_RETURN: 0.016 7_DAY_RETURN: 0.0154999999999999 | 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: Nestle LAST_PRICE: 80.0 PX_VOLUME: 4263190.0 VOLATILITY_10D: 10.931 VOLATILITY_30D: 9.244 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.00225
Predicted 2_DAY_RETURN: 0.0099999999999999
Predicted 7_DAY_RETURN: 0.0154999999999999 |
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: Judiciary Committee chairman says 'no reason to delay' Ford testimony https://t.co/LgoM7zKhZW" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Ford" STOCK: 19/09/2018 DATE: 9.78 | 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 0.0 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: 19/09/2018 1_DAY_RETURN: -0.0235173824130878 2_DAY_RETURN: -0.0337423312883435 3_DAY_RETURN: -0.0449897750511247 7_DAY_RETURN: 40111485.0 | 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: 19/09/2018 LAST_PRICE: -0.0204498977505111 PX_VOLUME: 17.855999999999995 VOLATILITY_10D: 23.16 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: -0.0235173824130878
Predicted 2_DAY_RETURN: -0.0337423312883435
Predicted 7_DAY_RETURN: 40111485.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Starbucks: @chocohyoo Hyungwon will always be our Starbucks king! 👑" 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: 19/09/2018 DATE: 55.43 | 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: 19/09/2018 1_DAY_RETURN: -0.0155150640447411 2_DAY_RETURN: -0.0122677250586325 3_DAY_RETURN: -0.008298755186722 7_DAY_RETURN: 7451644.0 | 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: 19/09/2018 LAST_PRICE: -0.0064946779722172 PX_VOLUME: 9.032 VOLATILITY_10D: 11.19 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: -0.0155150640447411
Predicted 2_DAY_RETURN: -0.0122677250586325
Predicted 7_DAY_RETURN: 7451644.0 |
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 Nike Free RN Running Shoes GS Airmax Jordan Vapormax Flyknit https://t.co/hcbHoIpgDl @eBay @NikeAirMax… https://t.co/v1O9NAR4lq" 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: 19/09/2018 DATE: 84.43 | 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 @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: 19/09/2018 1_DAY_RETURN: -0.0138576335425796 2_DAY_RETURN: -0.0111334833589957 3_DAY_RETURN: -0.0169371076631529 7_DAY_RETURN: 8053129.0 | 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: 19/09/2018 LAST_PRICE: 0.0098306289233684 PX_VOLUME: 17.913 VOLATILITY_10D: 19.231 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.4 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0138576335425796
Predicted 2_DAY_RETURN: -0.0111334833589957
Predicted 7_DAY_RETURN: 8053129.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @mindy_marvelmom: @Disney A spoonful of sugar isn’t enough to get the bad taste of Disney caving to alt-right scumbags out of my mouth.…" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Disney" STOCK: 19/09/2018 DATE: 109.79 | 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 -0.3499999999999999 and the TextBlob polarity score is @Disney. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 19/09/2018 1_DAY_RETURN: -0.003916567993442 2_DAY_RETURN: -0.0048273977593587 3_DAY_RETURN: -0.0030057382275253 7_DAY_RETURN: 5964771.0 | 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: 19/09/2018 LAST_PRICE: -0.0023681573913835 PX_VOLUME: 11.93 VOLATILITY_10D: 9.265 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.3499999999999999 TEXTBLOB_POLARITY: @Disney | Predicted 1_DAY_RETURN: -0.003916567993442
Predicted 2_DAY_RETURN: -0.0048273977593587
Predicted 7_DAY_RETURN: 5964771.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Starbucks: @hyungnyan *sips Starbucks like Hyungwon*" 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: 19/09/2018 DATE: 55.43 | 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: 19/09/2018 1_DAY_RETURN: -0.0155150640447411 2_DAY_RETURN: -0.0122677250586325 3_DAY_RETURN: -0.008298755186722 7_DAY_RETURN: 7451644.0 | 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: 19/09/2018 LAST_PRICE: -0.0064946779722172 PX_VOLUME: 9.032 VOLATILITY_10D: 11.19 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: -0.0155150640447411
Predicted 2_DAY_RETURN: -0.0122677250586325
Predicted 7_DAY_RETURN: 7451644.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Starbucks Monbebe should get discounts and a special card to buy at Starbucks, I mean, because of our king Hyungwon 👑
" STOCK: Starbucks DATE: 19/09/2018 | 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 0.02232142857142857. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Starbucks 1_DAY_RETURN: -0.0064946779722172 2_DAY_RETURN: -0.0155150640447411 3_DAY_RETURN: -0.0122677250586325 7_DAY_RETURN: -0.008298755186722 | 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: Starbucks LAST_PRICE: 55.43 PX_VOLUME: 7451644.0 VOLATILITY_10D: 9.032 VOLATILITY_30D: 11.19 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.02232142857142857 | Predicted 1_DAY_RETURN: -0.0064946779722172
Predicted 2_DAY_RETURN: -0.0155150640447411
Predicted 7_DAY_RETURN: -0.008298755186722 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @MOCHlROSE: @Starbucks @jaeminpic See Starbucks this is why youre the only coffee shop in N-city its cause you're the only intellectual…" 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: 19/09/2018 DATE: 55.43 | 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: 19/09/2018 1_DAY_RETURN: -0.0155150640447411 2_DAY_RETURN: -0.0122677250586325 3_DAY_RETURN: -0.008298755186722 7_DAY_RETURN: 7451644.0 | 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: 19/09/2018 LAST_PRICE: -0.0064946779722172 PX_VOLUME: 9.032 VOLATILITY_10D: 11.19 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: -0.0155150640447411
Predicted 2_DAY_RETURN: -0.0122677250586325
Predicted 7_DAY_RETURN: 7451644.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Ryanair Disgusted with Ryanair! 15 of us booked flights via the Ryanair App, there was no mention of the baggage c… https://t.co/TY8GXJZuD8
" STOCK: Ryanair DATE: 19/09/2018 | 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 -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: Ryanair 1_DAY_RETURN: -0.0123636363636363 2_DAY_RETURN: -0.0167272727272727 3_DAY_RETURN: -0.0392727272727272 7_DAY_RETURN: -0.0407272727272727 | 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: Ryanair LAST_PRICE: 13.75 PX_VOLUME: 1050957.0 VOLATILITY_10D: 22.627 VOLATILITY_30D: 30.478 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: -1.0 | Predicted 1_DAY_RETURN: -0.0123636363636363
Predicted 2_DAY_RETURN: -0.0167272727272727
Predicted 7_DAY_RETURN: -0.0407272727272727 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Vintage0Antique: Check out BMW / MINI COOPER S R56 R50 R53 PASSENGER AIRBAG ON OFF SWITCH BUTTON 2006 CAR https://t.co/jxmFCy9zwV @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: "BMW" STOCK: 19/09/2018 DATE: 83.45 | 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: 19/09/2018 1_DAY_RETURN: -0.0150988615937687 2_DAY_RETURN: -0.0117435590173757 3_DAY_RETURN: -0.028520071899341 7_DAY_RETURN: 1558066.0 | 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: 19/09/2018 LAST_PRICE: -0.0091072498502097 PX_VOLUME: 12.002 VOLATILITY_10D: 15.778 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0150988615937687
Predicted 2_DAY_RETURN: -0.0117435590173757
Predicted 7_DAY_RETURN: 1558066.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Apple: Introducing Apple Watch Series 4. Fundamentally redesigned and re-engineered to help you become even more active, healthy and co…
" STOCK: Apple DATE: 19/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Apple 1_DAY_RETURN: -0.0005953198699454 2_DAY_RETURN: -0.0022438979713331 3_DAY_RETURN: 0.0250492283738608 7_DAY_RETURN: 0.0123643357604065 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Apple LAST_PRICE: 218.37 PX_VOLUME: 27123833.0 VOLATILITY_10D: 27.976 VOLATILITY_30D: 19.631 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0005953198699454
Predicted 2_DAY_RETURN: -0.0022438979713331
Predicted 7_DAY_RETURN: 0.0123643357604065 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @csiltd: Intel and @SAP to partner on Enterprise #Blockchain Development https://t.co/QzamOEEFwk #TechNews #Partners by @uk_investing" 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: 19/09/2018 DATE: 46.15 | 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: 19/09/2018 1_DAY_RETURN: -0.0158179848320692 2_DAY_RETURN: -0.0132177681473456 3_DAY_RETURN: -0.0264355362946912 7_DAY_RETURN: 15918914.0 | 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: 19/09/2018 LAST_PRICE: -0.0010834236186348 PX_VOLUME: 22.648000000000003 VOLATILITY_10D: 19.575 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP | Predicted 1_DAY_RETURN: -0.0158179848320692
Predicted 2_DAY_RETURN: -0.0132177681473456
Predicted 7_DAY_RETURN: 15918914.0 |
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 eBay Template Listing Responsive 100% & Compatible with all browsers & eBay-app https://t.co/oT5NGsF0mI 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: 19/09/2018 DATE: 34.22 | 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 @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: 19/09/2018 1_DAY_RETURN: -0.0005844535359437 2_DAY_RETURN: -0.0035067212156632 3_DAY_RETURN: 0.0011689070718877 7_DAY_RETURN: 13455592.0 | 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: 19/09/2018 LAST_PRICE: -0.0029222676797195 PX_VOLUME: 11.962 VOLATILITY_10D: 14.171 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0005844535359437
Predicted 2_DAY_RETURN: -0.0035067212156632
Predicted 7_DAY_RETURN: 13455592.0 |
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: Tightening Texas race boosts Democrats' hopes of taking Senate: Reuters poll https://t.co/HdnermmEEK" 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: 19/09/2018 DATE: 50.0055 | 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: 19/09/2018 1_DAY_RETURN: 0.0024237333893272 2_DAY_RETURN: 0.0026437091919889 3_DAY_RETURN: -0.0039655637879832 7_DAY_RETURN: 7045324.0 | 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: 19/09/2018 LAST_PRICE: 0.0048454669986301 PX_VOLUME: 10.691 VOLATILITY_10D: 13.978 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0024237333893272
Predicted 2_DAY_RETURN: 0.0026437091919889
Predicted 7_DAY_RETURN: 7045324.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Kavanaugh Accuser Christine Blasey Ford is Moving Out of Her Home Due to Death Threats https://t.co/HWB1mpofmU via @Yahoo" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Ford" STOCK: 19/09/2018 DATE: 9.78 | 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 -0.125 and the TextBlob polarity score is @Yahoo. |
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