instruction
stringclasses 3
values | input
stringlengths 33
307
| output
stringlengths 66
248
|
|---|---|---|
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 0.25 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: 0.0155038759689922 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: 0.25 TEXTBLOB_POLARITY: @Apple | 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: "RT @Honda: Honda finishes the @IndyCar season strong with a dominating @RyanHunterReay victory at #SonomaGP! Congratulations to @scottdixon…" 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: "Honda" STOCK: 17/09/2018 DATE: 3217.0 | 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 0.5416666666666666 and the TextBlob polarity score is @Honda. |
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: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.018029219769972 7_DAY_RETURN: 6734300.0 | 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: 0.0 PX_VOLUME: 19.242 VOLATILITY_10D: 20.761 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.5416666666666666 TEXTBLOB_POLARITY: @Honda | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: 6734300.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Burberry: Serving spoon crested with Thomas Burberry Unicorn logo, 1874
Archive inspiration curated by Riccardo Tisci
#BurberryHeritage…
" STOCK: Burberry 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: Burberry 1_DAY_RETURN: 0.0208629682313892 2_DAY_RETURN: 0.0208629682313892 3_DAY_RETURN: 0.0208629682313892 7_DAY_RETURN: -0.0142247510668563 | 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: Burberry LAST_PRICE: 2109.0 PX_VOLUME: 1638559.0 VOLATILITY_10D: 34.569 VOLATILITY_30D: 28.105 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0208629682313892
Predicted 2_DAY_RETURN: 0.0208629682313892
Predicted 7_DAY_RETURN: -0.0142247510668563 |
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 Womens Nike Running Shorts Size M NWT #Nike https://t.co/0CnxXgXpwa via @eBay" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Nike" STOCK: 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 @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: 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: @eBay | 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 @Burberry: Burberry Wallpaper, 1998-2000
Archive inspiration curated by Riccardo Tisci
#BurberryHeritage https://t.co/xNxQZl3Naz
" STOCK: Burberry 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: Burberry 1_DAY_RETURN: 0.0208629682313892 2_DAY_RETURN: 0.0208629682313892 3_DAY_RETURN: 0.0208629682313892 7_DAY_RETURN: -0.0142247510668563 | 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: Burberry LAST_PRICE: 2109.0 PX_VOLUME: 1638559.0 VOLATILITY_10D: 34.569 VOLATILITY_30D: 28.105 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0208629682313892
Predicted 2_DAY_RETURN: 0.0208629682313892
Predicted 7_DAY_RETURN: -0.0142247510668563 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Walmart: As the storm continues along the East Coast, here’s how you can help—donate to the Walmart 2018 Hurricane Relief Fund, online…
" STOCK: Walmart 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: Walmart 1_DAY_RETURN: -0.0024256485973422 2_DAY_RETURN: -0.0024256485973422 3_DAY_RETURN: -0.0024256485973422 7_DAY_RETURN: 0.0219363003585742 | 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: Walmart LAST_PRICE: 94.82 PX_VOLUME: 5329819.0 VOLATILITY_10D: 12.857 VOLATILITY_30D: 30.135 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0024256485973422
Predicted 2_DAY_RETURN: -0.0024256485973422
Predicted 7_DAY_RETURN: 0.0219363003585742 |
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: RSLOVE Women Lace Teddy Lingerie Chemise V-... by RSLOVE for $15.39 https://t.co/Zw3sVHNg5Q 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 0.0 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: 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: 0.0 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: "@LauraLoomer @Kaepernick7 @Nike @USCG Does Nike support this behavior?" 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: "@X_TheArtist @amazon Not what I was told by Amazon 🤷🏽♀️ ... and this isn’t for a current order. I’m just browsing… https://t.co/7ZrerRPr8Y" 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 0.0 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: 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: 0.0 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: "Check out Nike Air Jordan Dub Zero Mens White Basketball Shoes Size 7.5 EUC 311046-106 #Nike https://t.co/aG3JZzrdjN via @eBay" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Nike" STOCK: 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 @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: 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: @eBay | 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 @Microsoft: From 23,500 global participants and 5,850 projects, the 2018 Microsoft Hackathon winner has emerged. Learn more about the te…
" STOCK: Microsoft 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: Microsoft 1_DAY_RETURN: 0.0109684323167469 2_DAY_RETURN: 0.0109684323167469 3_DAY_RETURN: 0.0109684323167469 7_DAY_RETURN: -0.0246120920278224 | 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: Microsoft LAST_PRICE: 112.14 PX_VOLUME: 20736516.0 VOLATILITY_10D: 22.448 VOLATILITY_30D: 16.375999999999998 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0109684323167469
Predicted 2_DAY_RETURN: 0.0109684323167469
Predicted 7_DAY_RETURN: -0.0246120920278224 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@ATT CEO calls @Netflix ‘the Walmart’ of SVOD while @HBO the ‘Tiffany’. Sounds like he’s never used HBO on Apple TV… https://t.co/AReMjdE7GU" 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 @ATT. |
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: @ATT | 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 @ATT: For just $49.99, get the Samsung Galaxy Express Prime 3! No contract, credit check or activation fee. Hurry, offer ends soon!
" STOCK: Samsung 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: Samsung 1_DAY_RETURN: 0.0155038759689922 2_DAY_RETURN: 0.0155038759689922 3_DAY_RETURN: 0.0155038759689922 7_DAY_RETURN: 0.0077519379844961 | 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: Samsung LAST_PRICE: 45150.0 PX_VOLUME: 8123384.0 VOLATILITY_10D: 33.013000000000005 VOLATILITY_30D: 27.312 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0155038759689922
Predicted 2_DAY_RETURN: 0.0155038759689922
Predicted 7_DAY_RETURN: 0.0077519379844961 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "It is absurd how @netflix just reused the @TheDefenders Facebook page as the @NXOnNetflix page like what the fuck i… https://t.co/Bd1TfGmlVI" 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: 17/09/2018 DATE: 160.58 | 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 -0.45 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: 17/09/2018 1_DAY_RETURN: 0.0108357205131397 2_DAY_RETURN: 0.0108357205131397 3_DAY_RETURN: 0.0224187320961514 7_DAY_RETURN: 21005321.0 | 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: 0.0108357205131397 PX_VOLUME: 24.277 VOLATILITY_10D: 20.157 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.45 TEXTBLOB_POLARITY: @netflix | Predicted 1_DAY_RETURN: 0.0108357205131397
Predicted 2_DAY_RETURN: 0.0108357205131397
Predicted 7_DAY_RETURN: 21005321.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @LifeatSAP: SAP is excited to partner with global music group Now United! Together, @SAP and @NowUnitedMusic will explore how data, tech…
" STOCK: SAP 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 0.1875. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: SAP 1_DAY_RETURN: 0.017766497461929 2_DAY_RETURN: 0.017766497461929 3_DAY_RETURN: 0.017766497461929 7_DAY_RETURN: -0.0040999609527528 | 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: SAP LAST_PRICE: 102.44 PX_VOLUME: 2070188.0 VOLATILITY_10D: 22.657 VOLATILITY_30D: 17.320999999999998 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.1875 | Predicted 1_DAY_RETURN: 0.017766497461929
Predicted 2_DAY_RETURN: 0.017766497461929
Predicted 7_DAY_RETURN: -0.0040999609527528 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Disney Smeg off, Disney. There is only one Mary Poppins and his name is Yondu. Now get yer shite straight &… https://t.co/NP0F1zobF2
" STOCK: Disney 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: Disney 1_DAY_RETURN: -0.0009144111192391 2_DAY_RETURN: -0.0009144111192391 3_DAY_RETURN: -0.0009144111192391 7_DAY_RETURN: 0.0120702267739576 | 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: Disney LAST_PRICE: 109.36 PX_VOLUME: 5592864.0 VOLATILITY_10D: 12.786 VOLATILITY_30D: 11.306 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0009144111192391
Predicted 2_DAY_RETURN: -0.0009144111192391
Predicted 7_DAY_RETURN: 0.0120702267739576 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Today's Shell Shocker: @HP Stream 11-y010wm Intel N3060 (1.60 GHz) 4GB RAM 32GB eMMC 11.6" $159.99…
" STOCK: Shell 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: Shell 1_DAY_RETURN: -0.0014152850788515 2_DAY_RETURN: -0.0014152850788515 3_DAY_RETURN: -0.0014152850788515 7_DAY_RETURN: -0.0186008896077638 | 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: Shell LAST_PRICE: 2473.0 PX_VOLUME: 4608560.0 VOLATILITY_10D: 16.511 VOLATILITY_30D: 17.215 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0014152850788515
Predicted 2_DAY_RETURN: -0.0014152850788515
Predicted 7_DAY_RETURN: -0.0186008896077638 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Expedia I shared some concerns in my survey regarding the car rental purchased through Expedia & I’m asking if any… https://t.co/YTWAuboxkA" 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: "Expedia" STOCK: 17/09/2018 DATE: 128.98 | 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 @Expedia. |
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: 0.0058923864164988 2_DAY_RETURN: 0.0058923864164988 3_DAY_RETURN: 0.0005427198015197 7_DAY_RETURN: 1071683.0 | 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: 0.0058923864164988 PX_VOLUME: 26.784 VOLATILITY_10D: 20.108 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Expedia | Predicted 1_DAY_RETURN: 0.0058923864164988
Predicted 2_DAY_RETURN: 0.0058923864164988
Predicted 7_DAY_RETURN: 1071683.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @REBELCHILD24: Check out Sony Betamax AG-400 VIdeo Cassette Tape Auto Changer Made In Japan #Sony https://t.co/lAyU8ZcL2z 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: "Sony" STOCK: 17/09/2018 DATE: 6630.0 | 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 @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: 17/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.0580693815987933 7_DAY_RETURN: 9555000.0 | 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: 0.0 PX_VOLUME: 21.709 VOLATILITY_10D: 20.477 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: 9555000.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@LoverOfTechBA @LenovoLegion @HP I didn't realise I'd end up with the Intel Optane model. I'm torn as the Omen 1070… https://t.co/EpGZFxEn9k" 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: 17/09/2018 DATE: 45.42 | 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 @HP. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 17/09/2018 1_DAY_RETURN: 0.0026420079260237 2_DAY_RETURN: 0.0026420079260237 3_DAY_RETURN: 0.0193747247908409 7_DAY_RETURN: 17603171.0 | 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: 0.0026420079260237 PX_VOLUME: 19.822 VOLATILITY_10D: 19.23 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @HP | Predicted 1_DAY_RETURN: 0.0026420079260237
Predicted 2_DAY_RETURN: 0.0026420079260237
Predicted 7_DAY_RETURN: 17603171.0 |
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: Youth activists and journalists protest in Yangon over the jailing of two Reuters reporters, Wa Lone and Kyaw Soe Oo https://t…
" STOCK: Reuters 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: Reuters 1_DAY_RETURN: 0.0002194439290837 2_DAY_RETURN: 0.0002194439290837 3_DAY_RETURN: 0.0002194439290837 7_DAY_RETURN: -0.0175794536644143 | 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: Reuters LAST_PRICE: 50.1267 PX_VOLUME: 2828945.0 VOLATILITY_10D: 11.155 VOLATILITY_30D: 16.894000000000002 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0002194439290837
Predicted 2_DAY_RETURN: 0.0002194439290837
Predicted 7_DAY_RETURN: -0.0175794536644143 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Check out Nike USA World Cup Away Jersey Kid's Soccer Jersey Size Large (14-16) Used #Nike https://t.co/mfPo3duiMe 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. |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.