Opinion Mining for Software Development
SKU: 52649492696

Opinion Mining for Software Development

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Description

Opinion Mining for Software DevelopmentOpinion mining, which uses computational methods to extract opinions and sentiments from natural language texts, can be applied to various software engineering (SE) tasks. For example, developers can mine user feedback from mobile app reviews to understand how to improve their products, and software team leaders can assess developers' mood and emotions by mining communication logs or commit messages. Also, the growing popularity of technical Q&A

Opinion mining, which uses computational methods to extract opinions and sentiments from natural language texts, can be applied to various software engineering (SE) tasks. For example, developers can mine user feedback from mobile app reviews to understand how to improve their products, and software team leaders can assess developers' mood and emotions by mining communication logs or commit messages. Also, the growing popularity of technical Q&A websites (e.g., Stack Overflow) and code-sharing platforms (e.g., GitHub) made available a plethora of information that can be mined to collect opinions of experienced developers (e.g., what they think about a specific software library). The latter can be used to assist software design decisions.

However, such a task is far from trivial due to three main reasons: First, the amount of information available online is huge; second, opinions are often embedded in unstructured data; and third, recent studies have indicated that opinion mining tools provide unreliable results when used out-of-the-box in the SE domain, since they are not designed to process SE datasets.

Despite all these challenges, we believe mining opinions from online resources enables developers to access peers' expertise with ease. The knowledge embedded in these opinions, once converted into actionable items, can facilitate software development activities.

We first investigated the feasibility of using state-of-the-art sentiment analysis tools to identify sentiment polarity in the software context. We also examined whether customizing a neural network model with SE data can improve its performance of sentiment polarity prediction. Based on the findings of these studies, we proposed a novel approach for recommending APIs with rationales by mining opinions from Q&A websites to support software design decisions. On the one hand, we shed light on the limitations researchers face when applying existing opinion mining techniques in SE context. On the other hand, we illustrate the promise of mining opinions from online resources to support software development activities.

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SKU: 52649492696

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Great for Kids, Smells Nice, and No Harsh Chemicals
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This sunscreen spray is easy to apply, not greasy, and doesn’t leave a sticky residue. The tropical fruit scent is light and pleasant, which makes it easier to convince kids to wear it. I also like that Alba Botanica avoids oxybenzone and other harsh chemicals. It holds up well for swimming and outdoor play. The 2-pack is convenient to keep one at home and one in the beach bag. It is a great deal!
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Erika C.
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Does not spray
Size: 5 Ounce (Pack of 2)
Does not spray!!! This is the second set I purchased and I have had issues that I was unable to spray with 3 of the 4 bottles. Was incredibly inconvenient when we brought a new bottle on vacation and it didn't work. Company would not send a replacement - only a physical coupon. I cannot find the sunscreen in stores and the coupon only covers about half a new bottle.
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Hands down best sunscreen ever! It’s easy to apply and smells great. Keeps the kids protected from Sunburn
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Really good coverage for a spray, smells great and don’t irritate mine or my kids sensitive skin.
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Whiting, US
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Bad packaging
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The spray nozzle on these suck.
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