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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: "RT @Reuters: Boeing 787 plant in South Carolina to reopen Sunday after storm-related closure https://t.co/6mVfuwiJWB" 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: "Boeing" STOCK: 16/09/2018 DATE: 359.8 | 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: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: -0.0120622568093386 3_DAY_RETURN: -0.0292384658143414 7_DAY_RETURN: 2835757.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 20.806 VOLATILITY_10D: 22.042 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: -0.0120622568093386
Predicted 7_DAY_RETURN: 2835757.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Shoutout to @netflix for filiming my obsession, my teacher in my hometown Louisville,KY! Next time call me for a movie!
" STOCK: Next DATE: 16/09/2018 | 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: Next 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: 0.0082242990654205 7_DAY_RETURN: 0.0183177570093457 | 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: Next LAST_PRICE: 5350.0 PX_VOLUME: 268593.0 VOLATILITY_10D: 14.282 VOLATILITY_30D: 15.157 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: 0.0183177570093457 |
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: The all-new iPhone XS, iPhone XS Max, iPhone XR and Apple Watch Series 4 are here. #AppleEvent
" STOCK: Apple DATE: 16/09/2018 | 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: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: 0.0114814152966404 7_DAY_RETURN: -0.0113473909935667 | 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: Apple LAST_PRICE: 223.84 PX_VOLUME: 31999289.0 VOLATILITY_10D: 25.688 VOLATILITY_30D: 17.88 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: -0.0113473909935667 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@businessinsider Google Pixel Fraud might happen again with the launch of Pixel 3 on 9 October 2018
@Google is Kil… https://t.co/htp7Fx7EJ8
" STOCK: Google DATE: 17/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Google 1_DAY_RETURN: 0.0156488450893666 2_DAY_RETURN: 0.0156488450893666 3_DAY_RETURN: 0.0156488450893666 7_DAY_RETURN: 0.0131312347499202 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Google LAST_PRICE: 1159.83 PX_VOLUME: 1704790.0 VOLATILITY_10D: 16.361 VOLATILITY_30D: 17.333 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0156488450893666
Predicted 2_DAY_RETURN: 0.0156488450893666
Predicted 7_DAY_RETURN: 0.0131312347499202 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @SAP: SAP technology allows @elephantsrhinos (ERP) to monitor elephants and rhinos with drones and sensors to reduce poaching. https://t…" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "SAP" STOCK: 17/09/2018 DATE: 102.44 | 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: 17/09/2018 1_DAY_RETURN: 0.017766497461929 2_DAY_RETURN: 0.017766497461929 3_DAY_RETURN: -0.0040999609527528 7_DAY_RETURN: 2070188.0 | 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: 17/09/2018 LAST_PRICE: 0.017766497461929 PX_VOLUME: 22.657 VOLATILITY_10D: 17.320999999999998 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP | Predicted 1_DAY_RETURN: 0.017766497461929
Predicted 2_DAY_RETURN: 0.017766497461929
Predicted 7_DAY_RETURN: 2070188.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@iDeplorableVET @Ford um I think because its a Ford. ha ha haaaaaaa jk" 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: 17/09/2018 DATE: 9.55 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Ford. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 17/09/2018 1_DAY_RETURN: -0.0104712041884818 2_DAY_RETURN: -0.0104712041884818 3_DAY_RETURN: -0.0178010471204188 7_DAY_RETURN: 29544428.0 | 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: 17/09/2018 LAST_PRICE: -0.0104712041884818 PX_VOLUME: 15.389 VOLATILITY_10D: 22.218000000000004 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Ford | Predicted 1_DAY_RETURN: -0.0104712041884818
Predicted 2_DAY_RETURN: -0.0104712041884818
Predicted 7_DAY_RETURN: 29544428.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@lawtonok @Nike Hey! Thanks for supporting Nike. I lived on Lawton 19 years. Have a good week." 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: 17/09/2018 DATE: 83.26 | 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 @Nike. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 17/09/2018 1_DAY_RETURN: 0.0027624309392263 2_DAY_RETURN: 0.0027624309392263 3_DAY_RETURN: -0.0139322603891425 7_DAY_RETURN: 4861055.0 | 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: 17/09/2018 LAST_PRICE: 0.0027624309392263 PX_VOLUME: 11.702 VOLATILITY_10D: 18.006 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Nike | Predicted 1_DAY_RETURN: 0.0027624309392263
Predicted 2_DAY_RETURN: 0.0027624309392263
Predicted 7_DAY_RETURN: 4861055.0 |
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: UK consumer spending grows at fastest pace since January: Visa https://t.co/gZWWYtwoQe https://t.co/qnJmhZrlc4" 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: "Visa" STOCK: 17/09/2018 DATE: 146.18 | 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: 17/09/2018 1_DAY_RETURN: 0.0113558626351073 2_DAY_RETURN: 0.0113558626351073 3_DAY_RETURN: -0.0143658503215213 7_DAY_RETURN: 7708643.0 | 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: 17/09/2018 LAST_PRICE: 0.0113558626351073 PX_VOLUME: 24.501 VOLATILITY_10D: 15.527 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0113558626351073
Predicted 2_DAY_RETURN: 0.0113558626351073
Predicted 7_DAY_RETURN: 7708643.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @treblepenguin7: I’m tellin’ ya, if @pepsi put @HunterHayes on commercials for their products, there’s no amount of Pepsi I wouldn’t buy…
" STOCK: Pepsi DATE: 17/09/2018 | 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: Pepsi 1_DAY_RETURN: -0.0071923743500867 2_DAY_RETURN: -0.0071923743500867 3_DAY_RETURN: -0.0071923743500867 7_DAY_RETURN: -0.0158578856152514 | 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: Pepsi LAST_PRICE: 115.4 PX_VOLUME: 3092582.0 VOLATILITY_10D: 12.625 VOLATILITY_30D: 14.112 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0071923743500867
Predicted 2_DAY_RETURN: -0.0071923743500867
Predicted 7_DAY_RETURN: -0.0158578856152514 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @SAP: SAP HANA is helping @ElephantsRhinos & People (ERP) preserve the world's ecosystem for future generations. https://t.co/H8kclZW3lr…" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "SAP" STOCK: 17/09/2018 DATE: 102.44 | 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: 17/09/2018 1_DAY_RETURN: 0.017766497461929 2_DAY_RETURN: 0.017766497461929 3_DAY_RETURN: -0.0040999609527528 7_DAY_RETURN: 2070188.0 | 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: 17/09/2018 LAST_PRICE: 0.017766497461929 PX_VOLUME: 22.657 VOLATILITY_10D: 17.320999999999998 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP | Predicted 1_DAY_RETURN: 0.017766497461929
Predicted 2_DAY_RETURN: 0.017766497461929
Predicted 7_DAY_RETURN: 2070188.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Buy any product from Amazon. For more details, Please click this picture or link
.LINK>
https://t.co/0swzfdlGnI via @amazon
" STOCK: Amazon DATE: 17/09/2018 | 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: Amazon 1_DAY_RETURN: 0.0325781041178598 2_DAY_RETURN: 0.0325781041178598 3_DAY_RETURN: 0.0325781041178598 7_DAY_RETURN: 0.0162366419815202 | 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: Amazon LAST_PRICE: 1908.03 PX_VOLUME: 7050192.0 VOLATILITY_10D: 26.273000000000003 VOLATILITY_30D: 21.683000000000003 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0325781041178598
Predicted 2_DAY_RETURN: 0.0325781041178598
Predicted 7_DAY_RETURN: 0.0162366419815202 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Triggmine: Next @Google, @facebook, @amazon, @Apple — it all could be decentralized. #Triggmine explores whether it will happen in a cl…
" STOCK: Next DATE: 17/09/2018 | 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: Next 1_DAY_RETURN: -0.0040953090096798 2_DAY_RETURN: -0.0040953090096798 3_DAY_RETURN: -0.0040953090096798 7_DAY_RETURN: 0.0059568131049888 | 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: Next LAST_PRICE: 5372.0 PX_VOLUME: 318190.0 VOLATILITY_10D: 12.408 VOLATILITY_30D: 15.076 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0040953090096798
Predicted 2_DAY_RETURN: -0.0040953090096798
Predicted 7_DAY_RETURN: 0.0059568131049888 |
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: Apple unveils a larger iPhone and a watch with a focus on health. More in this week's tech playlist via @ReutersTV https://t.c…" 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: 17/09/2018 DATE: 217.88 | 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: 17/09/2018 1_DAY_RETURN: 0.0273545070681109 2_DAY_RETURN: 0.0273545070681109 3_DAY_RETURN: 0.0020653570772903 7_DAY_RETURN: 37195133.0 | 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: 17/09/2018 LAST_PRICE: 0.0273545070681109 PX_VOLUME: 28.701 VOLATILITY_10D: 19.916 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0273545070681109
Predicted 2_DAY_RETURN: 0.0273545070681109
Predicted 7_DAY_RETURN: 37195133.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@CocaCola Coke sucks. Pepsi #1!" 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: 17/09/2018 DATE: 115.4 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.3 and the TextBlob polarity score is @CocaCola. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 17/09/2018 1_DAY_RETURN: -0.0071923743500867 2_DAY_RETURN: -0.0071923743500867 3_DAY_RETURN: -0.0158578856152514 7_DAY_RETURN: 3092582.0 | 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: 17/09/2018 LAST_PRICE: -0.0071923743500867 PX_VOLUME: 12.625 VOLATILITY_10D: 14.112 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.3 TEXTBLOB_POLARITY: @CocaCola | Predicted 1_DAY_RETURN: -0.0071923743500867
Predicted 2_DAY_RETURN: -0.0071923743500867
Predicted 7_DAY_RETURN: 3092582.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Audi: Electric is going Audi in 7 days: https://t.co/YoXyhOXtnG https://t.co/GkZK1dTtyu" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Audi" STOCK: 17/09/2018 DATE: 736.0 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Audi. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 17/09/2018 1_DAY_RETURN: -0.0081521739130434 2_DAY_RETURN: -0.0081521739130434 3_DAY_RETURN: -0.0489130434782608 7_DAY_RETURN: 5.0 | 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: 17/09/2018 LAST_PRICE: -0.0081521739130434 PX_VOLUME: 36.433 VOLATILITY_10D: 23.843000000000004 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Audi | Predicted 1_DAY_RETURN: -0.0081521739130434
Predicted 2_DAY_RETURN: -0.0081521739130434
Predicted 7_DAY_RETURN: 5.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @techgenez: Samsung Are you Ready?🧐🧐🧐 #TechGenez @Samsung @SamsungUS @SamsungMobile #tech #NEWS #technology #SmartCity #startups #Singap…" 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: "Samsung" STOCK: 17/09/2018 DATE: 45150.0 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Samsung. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 17/09/2018 1_DAY_RETURN: 0.0155038759689922 2_DAY_RETURN: 0.0155038759689922 3_DAY_RETURN: 0.0077519379844961 7_DAY_RETURN: 8123384.0 | 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: 17/09/2018 LAST_PRICE: 0.0155038759689922 PX_VOLUME: 33.013000000000005 VOLATILITY_10D: 27.312 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Samsung | Predicted 1_DAY_RETURN: 0.0155038759689922
Predicted 2_DAY_RETURN: 0.0155038759689922
Predicted 7_DAY_RETURN: 8123384.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "The pros and cons of Facebook Marketplace: How do you rate it?
@facebook
#Facebook #marketplace #buy #sell
https://t.co/wNMPpfFqyz
" STOCK: Facebook DATE: 17/09/2018 | 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: Facebook 1_DAY_RETURN: 0.0108357205131397 2_DAY_RETURN: 0.0108357205131397 3_DAY_RETURN: 0.0108357205131397 7_DAY_RETURN: 0.0224187320961514 | 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: Facebook LAST_PRICE: 160.58 PX_VOLUME: 21005321.0 VOLATILITY_10D: 24.277 VOLATILITY_30D: 20.157 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0108357205131397
Predicted 2_DAY_RETURN: 0.0108357205131397
Predicted 7_DAY_RETURN: 0.0224187320961514 |
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: Topic Trending Tracks (Today's Most Popular... by Various artists for $8.99 https://t.co/O1zbq9rpbl 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: 17/09/2018 DATE: 1908.03 | 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 0.3666666666666667 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: 17/09/2018 1_DAY_RETURN: 0.0325781041178598 2_DAY_RETURN: 0.0325781041178598 3_DAY_RETURN: 0.0162366419815202 7_DAY_RETURN: 7050192.0 | 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: 17/09/2018 LAST_PRICE: 0.0325781041178598 PX_VOLUME: 26.273000000000003 VOLATILITY_10D: 21.683000000000003 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.3666666666666667 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: 0.0325781041178598
Predicted 2_DAY_RETURN: 0.0325781041178598
Predicted 7_DAY_RETURN: 7050192.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @RepStevenSmith: So THESE are your "values" @Google?
Google Built China A Prototype Search Engine That Allows Government To Spy On Cit…
" STOCK: Google DATE: 17/09/2018 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Google 1_DAY_RETURN: 0.0156488450893666 2_DAY_RETURN: 0.0156488450893666 3_DAY_RETURN: 0.0156488450893666 7_DAY_RETURN: 0.0131312347499202 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Google LAST_PRICE: 1159.83 PX_VOLUME: 1704790.0 VOLATILITY_10D: 16.361 VOLATILITY_30D: 17.333 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0156488450893666
Predicted 2_DAY_RETURN: 0.0156488450893666
Predicted 7_DAY_RETURN: 0.0131312347499202 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Apple offering new AppleCare monthly plans along with theft and loss option @Apple #tech #mobile #smartphone… https://t.co/T3Rxc1Bfqj" 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: 17/09/2018 DATE: 217.88 | 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 @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: 17/09/2018 1_DAY_RETURN: 0.0273545070681109 2_DAY_RETURN: 0.0273545070681109 3_DAY_RETURN: 0.0020653570772903 7_DAY_RETURN: 37195133.0 | 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: 17/09/2018 LAST_PRICE: 0.0273545070681109 PX_VOLUME: 28.701 VOLATILITY_10D: 19.916 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.13636363636363635 TEXTBLOB_POLARITY: @Apple | Predicted 1_DAY_RETURN: 0.0273545070681109
Predicted 2_DAY_RETURN: 0.0273545070681109
Predicted 7_DAY_RETURN: 37195133.0 |
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: The all-new iPhone XS, iPhone XS Max, iPhone XR and Apple Watch Series 4 are here. #AppleEvent
" STOCK: Apple DATE: 17/09/2018 | 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: 0.0273545070681109 2_DAY_RETURN: 0.0273545070681109 3_DAY_RETURN: 0.0273545070681109 7_DAY_RETURN: 0.0020653570772903 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Apple LAST_PRICE: 217.88 PX_VOLUME: 37195133.0 VOLATILITY_10D: 28.701 VOLATILITY_30D: 19.916 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0273545070681109
Predicted 2_DAY_RETURN: 0.0273545070681109
Predicted 7_DAY_RETURN: 0.0020653570772903 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@dave_micheal1 @majestic_sawyer @Apple Samsung started the phablet trend.. samsung the first ones to start the beze… https://t.co/kbFUROngJw" 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. |
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