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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steve smith
San Leandro, US
★★★★★ 5
Great Quality
Size: 9.25 INCH
Why did you pick this product vs others?: Looked sturdy and was a great price for heavy duty brackets
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Reviewed in the United States on June 20, 2025
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Jason G
Massapequa, US
★★★★★ 5
Ignore the “Frequently returned item” message!
Color: Walnut Color, Color: Walnut Color
I usually don’t write reviews but I thought I should for these shelves. I was a little skeptical on these based on the “Frequently returned item” message but I decided to give them a shot and I’m glad I did! These shelves are solid and well made, beautiful color, fit perfectly in the corner of my wall, and are easy to hang. I’m not sure why they are frequently returned but I will be ordering another set for my wife’s side of the room.
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Reviewed in the United States on March 16, 2026
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Amazon Customer
Lake Worth, US
★★★★★ 5
Nice Shelves
Color: Acacia
Nice looking shelves and installed very easily.
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Reviewed in the United States on April 7, 2026
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Thomas Selden
Port Orchard, US
★★★★★ 4
Good looking, quality control needs improvement
Color: Acacia
The shelves are fine but one of the mounting blocks was glued on backwards which meant the holes for countersinking the mounting screwed ended up on the wrong side. It was easy to drill new countersinks so no big deal but a star is docked for quality control. They are cheap and looks good so I can't complain much.
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Reviewed in the United States on December 6, 2025
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Margaret S. Hastings
Phoenix, US
★★★★★ 5
Lovely, space saving and easy to install
Color: Acacia
LOVE THESE SHELVES! So easy to install and they look fantastic in any room. Good price point and very stable. Love the color of the wood, perfect for small spaces.
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Reviewed in the United States on February 10, 2026

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