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I'm 5'3", 140 pounds, and I ordered a small and I'm a medium. A high-low black dress with a stretchy cinched waist and ruffled hem that'll become your go-to dress.
Online reviews significantly impact consumers' decision-making process and firms' economic outcomes and are widely seen as crucial to the success of online markets. Firms, therefore, have a strong incentive to manipulate ratings using fake reviews. This presents a problem that academic researchers have tried to solve for over two decades and on which platforms expend a large amount of resources. Nevertheless, the prevalence of fake reviews is arguably higher than ever. To combat this, we collect a dataset of reviews for thousands of Amazon products and develop a general and highly accurate method for detecting fake reviews. A unique difference between previous datasets and ours is that we directly observe which sellers buy fake reviews. Thus, while prior research has trained models using laboratory-generated reviews or proxies for fake reviews, we are able to train a model using actual fake reviews. We show that products that buy fake reviews are highly clustered in the product reviewer network. Therefore, features constructed from this network are highly predictive of which products buy fake reviews. We show that our network-based approach is also successful at detecting fake review buyers even without ground truth data, as unsupervised clustering methods can accurately identify fake review buyers by identifying clusters of products that are closely connected in the network. While text or metadata can be manipulated to evade detection, network-based features are more costly to manipulate because these features result directly from the inherent limitations of buying reviews from online review marketplaces, making our detection approach more robust to manipulation. Keywords: machine learning; networks; online reviews; text analysis.
. And some sports race-old.
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Online reviews significantly impact consumers' decision-making process and firms' economic outcomes and are widely seen as crucial to the success of online markets. Firms, therefore, have a strong incentive to manipulate ratings using fake reviews. This presents a problem that academic researchers have tried to solve for over two decades and on which platforms expend a large amount of resources. Nevertheless, the prevalence of fake reviews is arguably higher than ever. To combat this, we collect a dataset of reviews for thousands of Amazon products and develop a general and highly accurate method for detecting fake reviews. A unique difference between previous datasets and ours is that we directly observe which sellers buy fake reviews. Thus, while prior research has trained models using laboratory-generated reviews or proxies for fake reviews, we are able to train a model using actual fake reviews. We show that products that buy fake reviews are highly clustered in the product reviewer network. Therefore, features constructed from this network are highly predictive of which products buy fake reviews. We show that our network-based approach is also successful at detecting fake review buyers even without ground truth data, as unsupervised clustering methods can accurately identify fake review buyers by identifying clusters of products that are closely connected in the network. While text or metadata can be manipulated to evade detection, network-based features are more costly to manipulate because these features result directly from the inherent limitations of buying reviews from online review marketplaces, making our detection approach more robust to manipulation. Keywords: machine learning; networks; online reviews; text analysis.
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All prize money available on OLBG. Australian Horse Racing tips of course count towards the overall Horse Racing and Horse Racing NAP tipster competitions.
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Maryland's law allows for up to 60 online sportsbooks and 30 retail sites. The regulation session ended in May without very much traction on the bill, though lawmakers may still opt to advance it in upcoming sessions.No movement
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Our plans will also include a restaurant and bar available to fans every day, helping to spur additional development in and around the arena district. Much of the sports wagering tax revenues would go to local, regional and state athletics initiatives, athletic programs at most University of North Carolina system schools and problem-gambling programs.
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bappleby17 with a profit of +657 (to 10pt stakes) over the past year for First & Anytime Goal Scorers. This is calculated by comparing the % of tips on a selection with the odds of that selection.
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Now you have three different tickets. Big paydays.
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bappleby17 with a profit of +657 (to 10pt stakes) over the past year for First & Anytime Goal Scorers. This is calculated by comparing the % of tips on a selection with the odds of that selection.
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Not Available in DC, NV, NY, KS, MS. Don't get confused by all the brackets and parentheses.
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Since it's close to the end of the year, it is almost time to wish COVID-19 a happy birthday and hope it disappears as vaccine trials start to show encouraging results. "Pretend You're Xyzzy" is a Cards Against Humanity clone available for your computer, or Google device that allows you and your friends to play together.
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Not Available in DC, NV, NY, KS, MS. Don't get confused by all the brackets and parentheses.
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The Trojans opened -2. And USC moneyline is already 8/1 tickets and 11/1 money," TwinSpires director of retail sports Zachary Lucas said.
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[Image] Promising review: "They arrived as expected and it is well-made. " -Amazon Customer 17.
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The most common side bets you'll find at real money blackjack tables are Perfect Pairs and 21+3. Total hand value is 21 (unsuited)
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20 (1/5) or greater. Bet365 online bookie offers at least 30 payment options, and each of them meets high-security standards.
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Play comfortably anywhere, anytime, and start getting lucky with Bet9ja! Everyone's favorite Nigerian bookmaker. Bet9ja never settles for less! All major leagues and events are covered by their sports betting pre-match markets.
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. Well but we will only want a couple of the best (In.
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(RM is a go-to for modern edge; MK, TB, and KS give good classics with a twist. Real talk: You might have your sights set on Gucci, Bottega Veneta, Saint Laurent, or Loewe.
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that say they are using affiliate marketing to make money, I want to know if this is pay its staff a living wage of $15 an hour, up from $9 an hour in 2013. The move comes
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Those who want to take part in the game of poker are notified shortly before the start and the organizer withholds 10% of players' winnings. Compared to the laws in some other countries where gambling is prohibited, laws in Qatar are not that severe, though.
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I use these for a lot of dishes. The chopsticks are great to hold.
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