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Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Apple 1_DAY_RETURN: 0.008030124308139 2_DAY_RETURN: 0.0016786135559386 3_DAY_RETURN: -0.0125215497686234 7_DAY_RETURN: -0.009300426458579 | 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: 220.42 PX_VOLUME: 23984706.0 VOLATILITY_10D: 20.27 VOLATILITY_30D: 20.4 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.008030124308139
Predicted 2_DAY_RETURN: 0.0016786135559386
Predicted 7_DAY_RETURN: -0.009300426458579 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @intel: Artificial intelligence powered by Intel Xeon is creating new ways to solve our toughest challenges. Learn how AI is aiding a Gr…" 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: 26/09/2018 DATE: 45.7 | 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 -0.2318181818181818 and the TextBlob polarity score is @intel. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 26/09/2018 1_DAY_RETURN: 0.0264770240700217 2_DAY_RETURN: 0.0210065645514221 3_DAY_RETURN: 0.0098468271334791 7_DAY_RETURN: 23957663.0 | 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: 26/09/2018 LAST_PRICE: 0.0045951859956234 PX_VOLUME: 21.185 VOLATILITY_10D: 20.327 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.2318181818181818 TEXTBLOB_POLARITY: @intel | Predicted 1_DAY_RETURN: 0.0264770240700217
Predicted 2_DAY_RETURN: 0.0210065645514221
Predicted 7_DAY_RETURN: 23957663.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @darrenrovell: JUST IN: @amazon announces that an @HannahStormESPN & Andrea Kremer will be the announcing team for Amazon Prime’s presen…" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Amazon" STOCK: 26/09/2018 DATE: 1974.85 | 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: 26/09/2018 1_DAY_RETURN: -0.0205028229992151 2_DAY_RETURN: -0.0303010355216851 3_DAY_RETURN: -0.0245233815226472 7_DAY_RETURN: 4313459.0 | 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: 26/09/2018 LAST_PRICE: -0.0001519102716661 PX_VOLUME: 27.409 VOLATILITY_10D: 22.276 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0205028229992151
Predicted 2_DAY_RETURN: -0.0303010355216851
Predicted 7_DAY_RETURN: 4313459.0 |
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 PAUL AND LINDA McCARTNEY Ram LP 1971 1st UK Apple -1/-1 Laminate Gatefld VG+/EX+ https://t.co/PxhDFuHmur @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: "Apple" STOCK: 26/09/2018 DATE: 220.42 | 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 @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: 26/09/2018 1_DAY_RETURN: 0.0016786135559386 2_DAY_RETURN: -0.0125215497686234 3_DAY_RETURN: -0.009300426458579 7_DAY_RETURN: 23984706.0 | 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: 26/09/2018 LAST_PRICE: 0.008030124308139 PX_VOLUME: 20.27 VOLATILITY_10D: 20.4 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.0016786135559386
Predicted 2_DAY_RETURN: -0.0125215497686234
Predicted 7_DAY_RETURN: 23984706.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Google Translator is nothing but a waist of time. @Google please delete this site.... #Google" 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: "Google" STOCK: 26/09/2018 DATE: 1194.06 | 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 @Google. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 26/09/2018 1_DAY_RETURN: -0.0121434433780547 2_DAY_RETURN: -0.0183742860492773 3_DAY_RETURN: -0.0165737065139104 7_DAY_RETURN: 1882524.0 | 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: 26/09/2018 LAST_PRICE: -0.0001423714051218 PX_VOLUME: 17.933 VOLATILITY_10D: 17.414 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Google | Predicted 1_DAY_RETURN: -0.0121434433780547
Predicted 2_DAY_RETURN: -0.0183742860492773
Predicted 7_DAY_RETURN: 1882524.0 |
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 Beautiful Pink Murano Glass Snail In Shell 6.5 inch Genuine Vintage Italian Art https://t.co/uqv7ZhtC3t @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: "Shell" STOCK: 26/09/2018 DATE: 2633.0 | 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 0.2875 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: 26/09/2018 1_DAY_RETURN: -0.0146221040638055 2_DAY_RETURN: -0.0244967717432586 3_DAY_RETURN: -0.0455753892897835 7_DAY_RETURN: 4420158.0 | 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: 26/09/2018 LAST_PRICE: 0.007785795670338 PX_VOLUME: 16.479 VOLATILITY_10D: 17.425 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.2875 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0146221040638055
Predicted 2_DAY_RETURN: -0.0244967717432586
Predicted 7_DAY_RETURN: 4420158.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: ".@Qualcomm accuses @Apple of stealing its secrets to help @intel - Reuters https://t.co/yDlgKakrN4" 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: 26/09/2018 DATE: 50.0606 | 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 @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: 26/09/2018 1_DAY_RETURN: -0.0002197336827765 2_DAY_RETURN: -0.0017598670411462 3_DAY_RETURN: -0.0011006659928167 7_DAY_RETURN: 4494517.0 | 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: 26/09/2018 LAST_PRICE: 0.0054993348062148 PX_VOLUME: 6.103 VOLATILITY_10D: 12.861 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Apple | Predicted 1_DAY_RETURN: -0.0002197336827765
Predicted 2_DAY_RETURN: -0.0017598670411462
Predicted 7_DAY_RETURN: 4494517.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Bosslogic: Marvel's Night Nurse (only on Disney Play)
"sometimes heroes need saving" @rosariodawson
Think about if @Disney you can hav…
" STOCK: Disney DATE: 26/09/2018 | 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: Disney 1_DAY_RETURN: -0.0137140873188091 2_DAY_RETURN: -0.0211787171252495 3_DAY_RETURN: -0.0417498481034631 7_DAY_RETURN: -0.0470445273847755 | The stock shows a consistent negative return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Disney LAST_PRICE: 115.21 PX_VOLUME: 11141544.0 VOLATILITY_10D: 18.798 VOLATILITY_30D: 13.007 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0137140873188091
Predicted 2_DAY_RETURN: -0.0211787171252495
Predicted 7_DAY_RETURN: -0.0470445273847755 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @intel: Artificial intelligence powered by Intel Xeon is creating new ways to solve our toughest challenges. Learn how AI is aiding a Gr…" 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: 26/09/2018 DATE: 45.7 | 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 -0.2318181818181818 and the TextBlob polarity score is @intel. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 26/09/2018 1_DAY_RETURN: 0.0264770240700217 2_DAY_RETURN: 0.0210065645514221 3_DAY_RETURN: 0.0098468271334791 7_DAY_RETURN: 23957663.0 | 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: 26/09/2018 LAST_PRICE: 0.0045951859956234 PX_VOLUME: 21.185 VOLATILITY_10D: 20.327 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.2318181818181818 TEXTBLOB_POLARITY: @intel | Predicted 1_DAY_RETURN: 0.0264770240700217
Predicted 2_DAY_RETURN: 0.0210065645514221
Predicted 7_DAY_RETURN: 23957663.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @brexit_sham: @carolecadwalla @pnhoward @facebook We certainly know that hidden amongst the Russian ads Facebook released to Congression…" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Facebook" STOCK: 26/09/2018 DATE: 166.95 | 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 0.015873015873015872 and the TextBlob polarity score is @facebook. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 26/09/2018 1_DAY_RETURN: -0.0092243186582808 2_DAY_RETURN: -0.0240790655884994 3_DAY_RETURN: -0.0233003893381251 7_DAY_RETURN: 25252231.0 | 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: 26/09/2018 LAST_PRICE: -0.0122192273135668 PX_VOLUME: 21.19400000000001 VOLATILITY_10D: 22.882 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.015873015873015872 TEXTBLOB_POLARITY: @facebook | Predicted 1_DAY_RETURN: -0.0092243186582808
Predicted 2_DAY_RETURN: -0.0240790655884994
Predicted 7_DAY_RETURN: 25252231.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@havinator @qikipedia @Tesco @sainsburys @waitrose Looks like the head of Tesco also leads a global programme that… https://t.co/cuRweCSnDA" 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: 26/09/2018 DATE: 243.9 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @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: 26/09/2018 1_DAY_RETURN: -0.018450184501845 2_DAY_RETURN: -0.029110291102911 3_DAY_RETURN: -0.033210332103321 7_DAY_RETURN: 21052680.0 | 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: 26/09/2018 LAST_PRICE: -0.009840098400984 PX_VOLUME: 11.279000000000002 VOLATILITY_10D: 17.223 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Tesco | Predicted 1_DAY_RETURN: -0.018450184501845
Predicted 2_DAY_RETURN: -0.029110291102911
Predicted 7_DAY_RETURN: 21052680.0 |
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: Facebook and Twitter must comply with EU consumer rules or face sanctions https://t.co/e4WvkuuuqO" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Facebook" STOCK: 26/09/2018 DATE: 166.95 | 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: 26/09/2018 1_DAY_RETURN: -0.0092243186582808 2_DAY_RETURN: -0.0240790655884994 3_DAY_RETURN: -0.0233003893381251 7_DAY_RETURN: 25252231.0 | 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: 26/09/2018 LAST_PRICE: -0.0122192273135668 PX_VOLUME: 21.19400000000001 VOLATILITY_10D: 22.882 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: -0.0092243186582808
Predicted 2_DAY_RETURN: -0.0240790655884994
Predicted 7_DAY_RETURN: 25252231.0 |
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: Dead Sea Mud Mask for Face & Body - 100% Na... by New York Biology for $13.95 https://t.co/wWLGXacAgz prin @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: 26/09/2018 DATE: 1974.85 | 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 -0.03181818181818183 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: 26/09/2018 1_DAY_RETURN: -0.0205028229992151 2_DAY_RETURN: -0.0303010355216851 3_DAY_RETURN: -0.0245233815226472 7_DAY_RETURN: 4313459.0 | 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: 26/09/2018 LAST_PRICE: -0.0001519102716661 PX_VOLUME: 27.409 VOLATILITY_10D: 22.276 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.03181818181818183 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0205028229992151
Predicted 2_DAY_RETURN: -0.0303010355216851
Predicted 7_DAY_RETURN: 4313459.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Bosslogic: Marvel's Night Nurse (only on Disney Play)
"sometimes heroes need saving" @rosariodawson
Think about if @Disney you can hav…
" STOCK: Disney DATE: 26/09/2018 | 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: Disney 1_DAY_RETURN: -0.0137140873188091 2_DAY_RETURN: -0.0211787171252495 3_DAY_RETURN: -0.0417498481034631 7_DAY_RETURN: -0.0470445273847755 | The stock shows a consistent negative return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Disney LAST_PRICE: 115.21 PX_VOLUME: 11141544.0 VOLATILITY_10D: 18.798 VOLATILITY_30D: 13.007 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0137140873188091
Predicted 2_DAY_RETURN: -0.0211787171252495
Predicted 7_DAY_RETURN: -0.0470445273847755 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @BMW: It is time. For a new thinking.
The all-new BMW 3 Series. The all-new BMW 3 Series. See you at #ParisMotorShow. #BMWParis https://…
" STOCK: BMW DATE: 26/09/2018 | 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: BMW 1_DAY_RETURN: 0.0033062054933876 2_DAY_RETURN: 0.0618006103763987 3_DAY_RETURN: 0.0901576805696846 7_DAY_RETURN: 0.0611648016276704 | 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: BMW LAST_PRICE: 78.64 PX_VOLUME: 3477206.0 VOLATILITY_10D: 37.439 VOLATILITY_30D: 24.645 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0033062054933876
Predicted 2_DAY_RETURN: 0.0618006103763987
Predicted 7_DAY_RETURN: 0.0611648016276704 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @BMW: It is time. For a new thinking.
The all-new BMW 3 Series. The all-new BMW 3 Series. See you at #ParisMotorShow. #BMWParis https://…
" STOCK: BMW DATE: 26/09/2018 | 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: BMW 1_DAY_RETURN: 0.0033062054933876 2_DAY_RETURN: 0.0618006103763987 3_DAY_RETURN: 0.0901576805696846 7_DAY_RETURN: 0.0611648016276704 | 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: BMW LAST_PRICE: 78.64 PX_VOLUME: 3477206.0 VOLATILITY_10D: 37.439 VOLATILITY_30D: 24.645 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0033062054933876
Predicted 2_DAY_RETURN: 0.0618006103763987
Predicted 7_DAY_RETURN: 0.0611648016276704 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@UPS If you need help from UPS they will not help you" 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: "UPS" STOCK: 26/09/2018 DATE: 116.7 | 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 @UPS. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 26/09/2018 1_DAY_RETURN: 0.0053984575835475 2_DAY_RETURN: 0.015338474721508 3_DAY_RETURN: 0.0132819194515852 7_DAY_RETURN: 2220578.0 | 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: 26/09/2018 LAST_PRICE: -0.0037703513281919 PX_VOLUME: 11.508 VOLATILITY_10D: 14.733 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @UPS | Predicted 1_DAY_RETURN: 0.0053984575835475
Predicted 2_DAY_RETURN: 0.015338474721508
Predicted 7_DAY_RETURN: 2220578.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Homegate with Lipton® Iced Tea from Walmart this NFL season. @Walmart #LiptonHomegating #Sponsored… https://t.co/JZzrXSkpHB" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Walmart" STOCK: 26/09/2018 DATE: 94.59 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Walmart. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 26/09/2018 1_DAY_RETURN: 0.0034887408816999 2_DAY_RETURN: 0.0138492441061423 3_DAY_RETURN: 0.0068717623427422 7_DAY_RETURN: 5918606.0 | 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: 26/09/2018 LAST_PRICE: 0.0053916904535362 PX_VOLUME: 8.972999999999997 VOLATILITY_10D: 29.613000000000003 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Walmart | Predicted 1_DAY_RETURN: 0.0034887408816999
Predicted 2_DAY_RETURN: 0.0138492441061423
Predicted 7_DAY_RETURN: 5918606.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@RolfeWinkler @Apple Apple had failed in protecting users as it provides no features. I have not seen a total solut… https://t.co/p8wnyqqdvH" 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: 26/09/2018 DATE: 220.42 | 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 -0.5 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: 26/09/2018 1_DAY_RETURN: 0.0016786135559386 2_DAY_RETURN: -0.0125215497686234 3_DAY_RETURN: -0.009300426458579 7_DAY_RETURN: 23984706.0 | 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: 26/09/2018 LAST_PRICE: 0.008030124308139 PX_VOLUME: 20.27 VOLATILITY_10D: 20.4 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.5 TEXTBLOB_POLARITY: @Apple | Predicted 1_DAY_RETURN: 0.0016786135559386
Predicted 2_DAY_RETURN: -0.0125215497686234
Predicted 7_DAY_RETURN: 23984706.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@netflix Put more naruto seasons on Netflix" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
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