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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: Starbucks 1_DAY_RETURN: 0.0123143788482433 2_DAY_RETURN: 0.0162984425932632 3_DAY_RETURN: 0.0162984425932632 7_DAY_RETURN: 0.0583122057225642 | 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: Starbucks LAST_PRICE: 55.22 PX_VOLUME: 14307985.0 VOLATILITY_10D: 23.916 VOLATILITY_30D: 17.298 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: -0.2 | Predicted 1_DAY_RETURN: 0.0123143788482433
Predicted 2_DAY_RETURN: 0.0162984425932632
Predicted 7_DAY_RETURN: 0.0583122057225642 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @blkahn: Rick Perry and Ryan Zinke have been confirmed to head Departments of Energy and Interior respectively per @Reuters" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Reuters" STOCK: 31/01/2017 DATE: 49.3887 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.2 and the TextBlob polarity score is @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0031221716708478 2_DAY_RETURN: 0.0031221716708478 3_DAY_RETURN: 0.0044605344947324 7_DAY_RETURN: 547029.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: -0.0026767256477695 PX_VOLUME: 9.665 VOLATILITY_10D: 9.094 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.2 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0031221716708478
Predicted 2_DAY_RETURN: 0.0031221716708478
Predicted 7_DAY_RETURN: 547029.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @EileenHamer1: At the Heart of Chicago: The third in the Chicago Stories Series by Eileen Ro... https://t.co/M1fs3dN5lI 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: 31/01/2017 DATE: 823.48 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @amazon. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0149244668965851 2_DAY_RETURN: 0.0149244668965851 3_DAY_RETURN: -0.0012629329188322 7_DAY_RETURN: 3137196.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: 0.0083790741730217 PX_VOLUME: 13.447 VOLATILITY_10D: 16.992 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: 0.0149244668965851
Predicted 2_DAY_RETURN: 0.0149244668965851
Predicted 7_DAY_RETURN: 3137196.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Check out blue fleece style pajama set 2 pc sleep wear 4/5 new Faded Glory Flame resistant #2piece https://t.co/uXPKeagCoN via @eBay" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "eBay" STOCK: 31/01/2017 DATE: 31.83 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.06818181818181818 and the TextBlob polarity score is @eBay. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.021363493559535 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: -0.0578071002199183 7_DAY_RETURN: 9469076.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: 0.0106817467797676 PX_VOLUME: 33.029 VOLATILITY_10D: 22.932 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.06818181818181818 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.021363493559535
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: 9469076.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @pepsi: Get ready to 💙 💙 💙 this exclusive new look #BTS of @ladygaga rehearsing for #PepsiHalftime! https://t.co/YHihjI9gW6" 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: 31/01/2017 DATE: 103.78 | 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 0.18522727272727274 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: 31/01/2017 1_DAY_RETURN: -0.0028907303912121 2_DAY_RETURN: -0.0028907303912121 3_DAY_RETURN: 0.0089612642127576 7_DAY_RETURN: 3846647.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: -0.0008672191173636 PX_VOLUME: 8.876 VOLATILITY_10D: 8.55 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.18522727272727274 TEXTBLOB_POLARITY: @pepsi | Predicted 1_DAY_RETURN: -0.0028907303912121
Predicted 2_DAY_RETURN: -0.0028907303912121
Predicted 7_DAY_RETURN: 3846647.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @CFR_IIGG: #Bangladesh to move forward with relocating thousands of #Rohingya to flooded island https://t.co/ZtM6gN84cO via @Reuters" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Reuters" STOCK: 31/01/2017 DATE: 49.3887 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0031221716708478 2_DAY_RETURN: 0.0031221716708478 3_DAY_RETURN: 0.0044605344947324 7_DAY_RETURN: 547029.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: -0.0026767256477695 PX_VOLUME: 9.665 VOLATILITY_10D: 9.094 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0031221716708478
Predicted 2_DAY_RETURN: 0.0031221716708478
Predicted 7_DAY_RETURN: 547029.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Lrihendry: Deplorables I am pleading with you NEVER do business with @Starbucks again, EVER! Let refugees patronize them with their $17…
" STOCK: Starbucks DATE: 31/01/2017 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Starbucks 1_DAY_RETURN: 0.0123143788482433 2_DAY_RETURN: 0.0162984425932632 3_DAY_RETURN: 0.0162984425932632 7_DAY_RETURN: 0.0583122057225642 | 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: Starbucks LAST_PRICE: 55.22 PX_VOLUME: 14307985.0 VOLATILITY_10D: 23.916 VOLATILITY_30D: 17.298 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0123143788482433
Predicted 2_DAY_RETURN: 0.0162984425932632
Predicted 7_DAY_RETURN: 0.0583122057225642 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@greeneyes0084 @Starbucks racist pigs like @realDonaldTrump drink Kool-Aid. Did you have one today?… https://t.co/0Ny4r2zyp5" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Starbucks" STOCK: 31/01/2017 DATE: 55.22 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Starbucks. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0162984425932632 2_DAY_RETURN: 0.0162984425932632 3_DAY_RETURN: 0.0583122057225642 7_DAY_RETURN: 14307985.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: 0.0123143788482433 PX_VOLUME: 23.916 VOLATILITY_10D: 17.298 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: 0.0162984425932632
Predicted 2_DAY_RETURN: 0.0162984425932632
Predicted 7_DAY_RETURN: 14307985.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Who is the real buyer of a 19.5 percent stake in Rosneft? Journalists, truth-seekers - we need you. https://t.co/Vh6hYBQOx7 via @Reuters
" STOCK: Reuters DATE: 31/01/2017 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.2. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Reuters 1_DAY_RETURN: -0.0026767256477695 2_DAY_RETURN: 0.0031221716708478 3_DAY_RETURN: 0.0031221716708478 7_DAY_RETURN: 0.0044605344947324 | 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: Reuters LAST_PRICE: 49.3887 PX_VOLUME: 547029.0 VOLATILITY_10D: 9.665 VOLATILITY_30D: 9.094 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.2 | Predicted 1_DAY_RETURN: -0.0026767256477695
Predicted 2_DAY_RETURN: 0.0031221716708478
Predicted 7_DAY_RETURN: 0.0044605344947324 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "4th time in 3 months I've had to mention wheat products in the #freefrom section at @Tesco. I don't get how it always ends up back there!" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Tesco" STOCK: 31/01/2017 DATE: 194.6 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 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: 31/01/2017 1_DAY_RETURN: 0.0614080164439877 2_DAY_RETURN: 0.0614080164439877 3_DAY_RETURN: -0.0125899280575539 7_DAY_RETURN: 79257504.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: 0.0164439876670093 PX_VOLUME: 60.469 VOLATILITY_10D: 39.887 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Tesco | Predicted 1_DAY_RETURN: 0.0614080164439877
Predicted 2_DAY_RETURN: 0.0614080164439877
Predicted 7_DAY_RETURN: 79257504.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Google: "If you have the feeling that something is wrong, don't be afraid to speak up." - Fred Korematsu #GoogleDoodle…
" STOCK: Google DATE: 31/01/2017 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is -0.55. |
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: 0.0044379960740803 2_DAY_RETURN: 0.0302856655165265 3_DAY_RETURN: 0.0302856655165265 7_DAY_RETURN: 0.0357721991245929 | 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: 820.19 PX_VOLUME: 2020180.0 VOLATILITY_10D: 21.549 VOLATILITY_30D: 14.953 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: -0.55 | Predicted 1_DAY_RETURN: 0.0044379960740803
Predicted 2_DAY_RETURN: 0.0302856655165265
Predicted 7_DAY_RETURN: 0.0357721991245929 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @drewneeds2: @FoxNews #MAGA Monday Night Beat Down BYE BYE @SallyQYates don't worry you'll be on @CBS @ABC @NBC @CNN tomorrow with a cro…" 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: "CBS" STOCK: 31/01/2017 DATE: 64.49 | 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 -0.1555555555555556 and the TextBlob polarity score is @CBS. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0038765700108543 2_DAY_RETURN: 0.0038765700108543 3_DAY_RETURN: -0.0234144828655605 7_DAY_RETURN: 3523867.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: -0.0013955652039074 PX_VOLUME: 16.338 VOLATILITY_10D: 16.302 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.1555555555555556 TEXTBLOB_POLARITY: @CBS | Predicted 1_DAY_RETURN: 0.0038765700108543
Predicted 2_DAY_RETURN: 0.0038765700108543
Predicted 7_DAY_RETURN: 3523867.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@rockyR5 @netflix I agree and if you do binge watch it all then Crave Television 📺 has whatever they didn't damn them to T.V Hell" 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: "Netflix" STOCK: 31/01/2017 DATE: 140.71 | 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 @netflix. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0123658588586453 2_DAY_RETURN: 0.0123658588586453 3_DAY_RETURN: -0.0042640892616018 7_DAY_RETURN: 4411631.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: 0.0036244758723615 PX_VOLUME: 27.398000000000003 VOLATILITY_10D: 24.135 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @netflix | Predicted 1_DAY_RETURN: 0.0123658588586453
Predicted 2_DAY_RETURN: 0.0123658588586453
Predicted 7_DAY_RETURN: 4411631.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@pepsi FOLLOW ME , IM YOUR FAN PEPSI
" STOCK: Pepsi DATE: 31/01/2017 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Pepsi 1_DAY_RETURN: -0.0008672191173636 2_DAY_RETURN: -0.0028907303912121 3_DAY_RETURN: -0.0028907303912121 7_DAY_RETURN: 0.0089612642127576 | 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: Pepsi LAST_PRICE: 103.78 PX_VOLUME: 3846647.0 VOLATILITY_10D: 8.876 VOLATILITY_30D: 8.55 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0008672191173636
Predicted 2_DAY_RETURN: -0.0028907303912121
Predicted 7_DAY_RETURN: 0.0089612642127576 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @nikitakhara: Thank you, @Starbucks CEO for committing to hire 10,000 refugees.
To all those tweeting #boycottstarbucks, thanks for the…
" STOCK: Starbucks DATE: 31/01/2017 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.2. |
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: 0.0123143788482433 2_DAY_RETURN: 0.0162984425932632 3_DAY_RETURN: 0.0162984425932632 7_DAY_RETURN: 0.0583122057225642 | 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: Starbucks LAST_PRICE: 55.22 PX_VOLUME: 14307985.0 VOLATILITY_10D: 23.916 VOLATILITY_30D: 17.298 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.2 | Predicted 1_DAY_RETURN: 0.0123143788482433
Predicted 2_DAY_RETURN: 0.0162984425932632
Predicted 7_DAY_RETURN: 0.0583122057225642 |
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: Trump meets with top drugmakers, calls on pharmaceutical industry to boost U.S. production, lower prices…
" STOCK: Reuters DATE: 31/01/2017 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.5. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Reuters 1_DAY_RETURN: -0.0026767256477695 2_DAY_RETURN: 0.0031221716708478 3_DAY_RETURN: 0.0031221716708478 7_DAY_RETURN: 0.0044605344947324 | 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: Reuters LAST_PRICE: 49.3887 PX_VOLUME: 547029.0 VOLATILITY_10D: 9.665 VOLATILITY_30D: 9.094 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.5 | Predicted 1_DAY_RETURN: -0.0026767256477695
Predicted 2_DAY_RETURN: 0.0031221716708478
Predicted 7_DAY_RETURN: 0.0044605344947324 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Lrihendry: We have 93 Million unemployed American citizens and @Starbucks offers to hire 10k #Syrianrefugees #BoycottStarbucks #MAGA" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Starbucks" STOCK: 31/01/2017 DATE: 55.22 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.05 and the TextBlob polarity score is @Starbucks. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0162984425932632 2_DAY_RETURN: 0.0162984425932632 3_DAY_RETURN: 0.0583122057225642 7_DAY_RETURN: 14307985.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: 0.0123143788482433 PX_VOLUME: 23.916 VOLATILITY_10D: 17.298 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.05 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: 0.0162984425932632
Predicted 2_DAY_RETURN: 0.0162984425932632
Predicted 7_DAY_RETURN: 14307985.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Lrihendry: We have 93 Million unemployed American citizens and @Starbucks offers to hire 10k #Syrianrefugees #BoycottStarbucks #MAGA" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Starbucks" STOCK: 31/01/2017 DATE: 55.22 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.05 and the TextBlob polarity score is @Starbucks. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0162984425932632 2_DAY_RETURN: 0.0162984425932632 3_DAY_RETURN: 0.0583122057225642 7_DAY_RETURN: 14307985.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: 0.0123143788482433 PX_VOLUME: 23.916 VOLATILITY_10D: 17.298 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.05 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: 0.0162984425932632
Predicted 2_DAY_RETURN: 0.0162984425932632
Predicted 7_DAY_RETURN: 14307985.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Check out Jelly The Pug Floral Outfit 18 Months Snap Together Crotch One Piece https://t.co/J7HUltu78C @eBay" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "eBay" STOCK: 31/01/2017 DATE: 31.83 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @eBay. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.021363493559535 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: -0.0578071002199183 7_DAY_RETURN: 9469076.0 | The stock shows a consistent positive return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 31/01/2017 LAST_PRICE: 0.0106817467797676 PX_VOLUME: 33.029 VOLATILITY_10D: 22.932 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.021363493559535
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: 9469076.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Check out Rare Vintage Lithograph Girl "Lovely To Look At" 9 x 7 1950s https://t.co/2FxdgUYJZO @eBay
" STOCK: eBay DATE: 31/01/2017 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.4. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: eBay 1_DAY_RETURN: 0.0106817467797676 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: 0.021363493559535 7_DAY_RETURN: -0.0578071002199183 | The stock shows a consistent negative return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: eBay LAST_PRICE: 31.83 PX_VOLUME: 9469076.0 VOLATILITY_10D: 33.029 VOLATILITY_30D: 22.932 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.4 | Predicted 1_DAY_RETURN: 0.0106817467797676
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: -0.0578071002199183 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Reuters: BREAKING: President Trump to sign executive order on cybersecurity - White House https://t.co/VckjA1Rpva" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Reuters" STOCK: 31/01/2017 DATE: 49.3887 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 31/01/2017 1_DAY_RETURN: 0.0031221716708478 2_DAY_RETURN: 0.0031221716708478 3_DAY_RETURN: 0.0044605344947324 7_DAY_RETURN: 547029.0 | The stock shows a consistent positive return trend over the specified periods. |
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