Ruben stranders thesis

A decentralised coordination algorithm for maximising sensor coverage in large sensor networks, A decentralised coordination algorithm for mobile sensors, A family of graphical-game-based algorithms for distributed constraint optimization problems, A hybrid continuous max-sum algorithm for decentralised coordination,

Ruben stranders thesis

The impact of online reviews: An annotated bibliography A few weeks Ruben stranders thesis, I received some questions about online consumer reviews, their impact on sales, and other related questions.

At that point, I realized that while I had a good grasp of the technical literature within Computer Science venues, my grasp of the overall empirical literature within Marketing and Information Systems venues was rather shaky, so I had to do a better work in preparing a literature review.

So, I did whatever a self-respecting professor would do in such a situation: I asked my PhD student, Beibei Lito compile a list of such papers, write a brief summary of each, and send me the list. She had passed her qualification exam by studying exactly this area, so she was the resident expert in the topic.

Beibei did not disappoint me. A few hours later I had a very good list of papers in my mailbox, together with the description. It was so good, that I thought that many other Ruben stranders thesis would be interested in the list.

So, without further ado, I present you Beibei's annotated bibliography about online reviews and their business impact. User behavior and online reviews Nan Hu, Paul Pavlou and Jie Zhang, in their paper " Overcoming the J-shaped distribution of product reviews " have shown that the graphical representation of product reviews has a J-shaped distribution: What can explain this distribution?

They attribute this rating distribution into two biases: People that buy a product do not constitute a random sample of the population.

Decentralised coordination of information gathering agents

People buy products that they believe they will enjoy. So, the reviews are written by people that are more likely to like the product. Since only people with higher product valuations purchase a product, those with lower valuations are less likely to purchase the product, and they will not write a negative product review.

Purchasing bias causes the positive skewness in the distribution of product reviews and inflates the average. Rather, early buyers buyers who also post the first reviews self-select product that they believe they may enjoy, in the absence of any existing information.

This is in contrast to other buyers that wait for more signals about the quality of a product to emerge, before being convinced to buy, and therefore have a lower prior expectation about the product quality. As a consequence, the preferences of early buyers systematically differ from the broader consumer population, the early reviews can be biased, either in a positive or negative way.

Such bias in reviews will affect sales and reduce consumer surplus, even if all reviews are truthful. Moe and Michael Trusov in their paper " Measuring the Value of Social Dynamics in Online Product Ratings Forums ", looked into how social influences affect the subsequent ratings and sales.

They demonstrated that reviewer rating behavior is significantly affected by previous ratings. In other words, product reviews not only reflect the customers' experience with the product, but they also affect the ratings of later reviews as well.

The recommendation of the authors to owners of review websites is that volume of previously posted reviews should become less prevalent in order to encourage posting of reviews for lesser-known products.

Online Book Reviews " have first demonstrated that online ratings have significant impact on book sales. The key trick was to monitor the sales of the same book in parallel on Amazon. Since the two sites were selling the same book, any external effect would be similar to both websites.

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However, effects specific to Amazon or on BN. Through this "differences in differences" method, Chevalier and Mayzlin could isolate and measure the effect of product reviews, without worrying about other confounding factors.

Ruben stranders thesis

Yong Liu, in the paper " Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue " have looked at the same topic, but focused on the movie box office. Different from Chevalier and Mayzlin, his finding suggested that the valence of reviews does not matter for box office sales, however the review volume does.

Accounting for Sequential Rollout and Aggregation Across Local Markets " have further studied the impact valence, volume, and variance of online reviews by looking at the local geographic movie box office, rather than the national-level aggregate box office performance.

After accounting for various potential complications in the analysis, they suggested that it is the valence that seems to matter and not the volume.Francesco Maria Delle Fave. Kathryn Sarah Macarthur. Long Tran-Thanh.

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It is in need of more than to answer the counter-argument, however. Ruben Stranders, Sarvapali Ramchurn, Bing Shi, Nicholas Jennings (University of Southampton) In this paper we develop a novel model of geospatial data creation, . In this thesis, we therefore propose a new approach to trust in Multi-Agent Systems based on argumentation that aims to expose the rationale behind these decisions.

Our solution features a clear separation of opponent modeling and decision making. Specific instantiations of this generic problem span a broad spectrum of concrete application domains, of which we study three canonical examples: monitoring environmental phenomena, wide area surveillance, and search and patrol.

The main contributions of this thesis are decentralised coordination algorithms that solve this general problem with additional constraints and requirements, and can be . In this thesis, we therefore propose a new approach to trust in Multi-Agent Systems based on argumentation that aims to expose the rationale behind these decisions.

Argumentation based decision making for trust in multi-agent systems () Cached. Download Links {Ruben Stranders and Ruben Stranders and Ruben Stranders and Msc.

Decentralised coordination of information gathering agents - ePrints Soton