Datasets:
moqarashad
/
tweet_dataset

Dataset card Data Studio Files Community
2
instruction
stringclasses
3 values
input
stringlengths
33
307
output
stringlengths
66
248
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @trvo512: are you fucking kidding me? @McDonalds https://t.co/YgNCoLqJhr" 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: "McDonald's" STOCK: 31/01/2017 DATE: 122.57
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 -0.6 and the TextBlob polarity score is @McDonalds.
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: 0.002365994941666 2_DAY_RETURN: 0.002365994941666 3_DAY_RETURN: -0.0124010769356285 7_DAY_RETURN: 3733323.0
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: 0.0036713714612058 PX_VOLUME: 7.972 VOLATILITY_10D: 9.585 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.6 TEXTBLOB_POLARITY: @McDonalds
Predicted 1_DAY_RETURN: 0.002365994941666 Predicted 2_DAY_RETURN: 0.002365994941666 Predicted 7_DAY_RETURN: 3733323.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @DrJimmyStar: Check out BBetsey Johnson Multi-Color Polka Dot Tote Bag NWT https://t.co/rI8FkTdPSY @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: "RT @FresnoStateCHHS: CHHS students! We're giving away a few @Starbucks gift cards & YOU could be the lucky winner. Enter by Feb.1 at 5 p… " 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: "RT @DrJimmyStar: Check out g By Marciano Ladies Animal Print Purse NWT https://t.co/9g9PqwAdex @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: "@Google supplement education with curated grade-appropriate content. Allow content producers to compete for course slots." 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: 31/01/2017 DATE: 820.19
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: 31/01/2017 1_DAY_RETURN: 0.0302856655165265 2_DAY_RETURN: 0.0302856655165265 3_DAY_RETURN: 0.0357721991245929 7_DAY_RETURN: 2020180.0
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: 0.0044379960740803 PX_VOLUME: 21.549 VOLATILITY_10D: 14.953 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Google
Predicted 1_DAY_RETURN: 0.0302856655165265 Predicted 2_DAY_RETURN: 0.0302856655165265 Predicted 7_DAY_RETURN: 2020180.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "And I'm hoping no one noticed my earlier tweet that said @netflix instead of @AmazonVideo I have both, and I love them equally. 😏 " STOCK: Netflix 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 0.16666666666666666.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Netflix 1_DAY_RETURN: 0.0036244758723615 2_DAY_RETURN: 0.0123658588586453 3_DAY_RETURN: 0.0123658588586453 7_DAY_RETURN: -0.0042640892616018
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: Netflix LAST_PRICE: 140.71 PX_VOLUME: 4411631.0 VOLATILITY_10D: 27.398000000000003 VOLATILITY_30D: 24.135 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.16666666666666666
Predicted 1_DAY_RETURN: 0.0036244758723615 Predicted 2_DAY_RETURN: 0.0123658588586453 Predicted 7_DAY_RETURN: -0.0042640892616018
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @DrJimmyStar: Check out g By Marciano Ladies Animal Print Purse NWT https://t.co/9g9PqwAdex @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: "RT @DrJimmyStar: Check out Betsey Johnson Cosmetic Bag NWT https://t.co/3WNMpr9Wzw @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: "RT @57Veronica: @netflix The chemistry of #BatB is really special, don't let it go to waste! Please give Beauty and the Beast a new home! #… " STOCK: Netflix 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 0.053571428571428575.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Netflix 1_DAY_RETURN: 0.0036244758723615 2_DAY_RETURN: 0.0123658588586453 3_DAY_RETURN: 0.0123658588586453 7_DAY_RETURN: -0.0042640892616018
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: Netflix LAST_PRICE: 140.71 PX_VOLUME: 4411631.0 VOLATILITY_10D: 27.398000000000003 VOLATILITY_30D: 24.135 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.053571428571428575
Predicted 1_DAY_RETURN: 0.0036244758723615 Predicted 2_DAY_RETURN: 0.0123658588586453 Predicted 7_DAY_RETURN: -0.0042640892616018
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Disney: He's a real pug! Get Pinocchio on Blu-ray, Digital HD, and @DisneyAnywhere: https://t.co/qGUyckyAYm (🐶: itsdougthe… " STOCK: Disney 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 0.25.
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: 0.0026208766380478 2_DAY_RETURN: -0.0122006326253954 3_DAY_RETURN: -0.0122006326253954 7_DAY_RETURN: -0.0248531405332128
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: 110.65 PX_VOLUME: 8485838.0 VOLATILITY_10D: 12.229 VOLATILITY_30D: 12.982 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.25
Predicted 1_DAY_RETURN: 0.0026208766380478 Predicted 2_DAY_RETURN: -0.0122006326253954 Predicted 7_DAY_RETURN: -0.0248531405332128
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @trvo512: are you fucking kidding me? @McDonalds https://t.co/YgNCoLqJhr" 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: "McDonald's" STOCK: 31/01/2017 DATE: 122.57
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 -0.6 and the TextBlob polarity score is @McDonalds.
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: 0.002365994941666 2_DAY_RETURN: 0.002365994941666 3_DAY_RETURN: -0.0124010769356285 7_DAY_RETURN: 3733323.0
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: 0.0036713714612058 PX_VOLUME: 7.972 VOLATILITY_10D: 9.585 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.6 TEXTBLOB_POLARITY: @McDonalds
Predicted 1_DAY_RETURN: 0.002365994941666 Predicted 2_DAY_RETURN: 0.002365994941666 Predicted 7_DAY_RETURN: 3733323.0
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 this Amazon deal: Honor 5X Unlocked Smartphone, 16GB Sunset Go... by Huawei https://t.co/yZNodMGLKt via @amazon " STOCK: Amazon 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: Amazon 1_DAY_RETURN: 0.0083790741730217 2_DAY_RETURN: 0.0149244668965851 3_DAY_RETURN: 0.0149244668965851 7_DAY_RETURN: -0.0012629329188322
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: Amazon LAST_PRICE: 823.48 PX_VOLUME: 3137196.0 VOLATILITY_10D: 13.447 VOLATILITY_30D: 16.992 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: 0.0083790741730217 Predicted 2_DAY_RETURN: 0.0149244668965851 Predicted 7_DAY_RETURN: -0.0012629329188322
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @DrJimmyStar: Check out g By Marciano Ladies Animal Print Purse NWT https://t.co/9g9PqwAdex @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: "RT @Starbucks: We're sending out exclusive offers, only on Twitter. 🙌 https://t.co/PhBJznMBOx " 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 0.05.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 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: 0.05
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 @DrJimmyStar: Check out g By Marciano Ladies Animal Print Purse NWT https://t.co/9g9PqwAdex @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: "RT @trvo512: are you fucking kidding me? @McDonalds https://t.co/YgNCoLqJhr" 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: "McDonald's" STOCK: 31/01/2017 DATE: 122.57
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 -0.6 and the TextBlob polarity score is @McDonalds.
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: 0.002365994941666 2_DAY_RETURN: 0.002365994941666 3_DAY_RETURN: -0.0124010769356285 7_DAY_RETURN: 3733323.0
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: 0.0036713714612058 PX_VOLUME: 7.972 VOLATILITY_10D: 9.585 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.6 TEXTBLOB_POLARITY: @McDonalds
Predicted 1_DAY_RETURN: 0.002365994941666 Predicted 2_DAY_RETURN: 0.002365994941666 Predicted 7_DAY_RETURN: 3733323.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @DrJimmyStar: Check out Westland Giftware Ceramic Spiderman Cookie Jar NIB Multi-Color https://t.co/IB65e9yvXS @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: "Is maintaining a flagship @Nike store in Trump Tower doing 'everything in our power'? https://t.co/vT87ZQX3GT" 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: 31/01/2017 DATE: 52.9
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 @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: 31/01/2017 1_DAY_RETURN: 0.0054820415879016 2_DAY_RETURN: 0.0054820415879016 3_DAY_RETURN: 0.0103969754253308 7_DAY_RETURN: 12342873.0
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: 0.0034026465028355 PX_VOLUME: 8.853 VOLATILITY_10D: 15.503 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Nike
Predicted 1_DAY_RETURN: 0.0054820415879016 Predicted 2_DAY_RETURN: 0.0054820415879016 Predicted 7_DAY_RETURN: 12342873.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @MarkSimoneNY: Hey @Starbucks, instead of hiring 10,000 refugees, how about hiring 10,000 veterans. " 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: "RT @MarkSimoneNY: Hey @Starbucks, instead of hiring 10,000 refugees, how about hiring 10,000 veterans. " 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: "Look what I found on @eBay! https://t.co/8UqHdpR6Sm 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.