Basic tasks of sentiment analysis

Subjectivity detection is the task of identifying objective and subjective sentences. Objective sentences are those which do not exhibit any sentiment. So, it is desired for a sentiment analysis engine to find and separate the objective sentences for further analysis, e.g., polarity detection. In subjective sentences, opinions can often be expressed on one or multiple topics. Aspect extraction is a subtask of sentiment analysis that consists in identifying opinion targets in opinionated text, i.e., in detecting the specific aspects of a product or service the opinion holder is either praising or complaining about

A comparative study of Persian sentiment analysis based on different feature combinations

In recent years, the use of internet and correspondingly the number of online reviews, comments and opinions have increased significantly. It is indeed very difficult for humans to read these opinions and classify them accurately. Consequently, there is a need for an automated system to process this big data. In this paper, a novel sentiment analysis framework for Persian language has been proposed. The proposed framework comprises three basic steps: pre-processing, feature extraction, and support vector machine (SVM) based classification. The performance of the proposed framework has been evaluated taking into account different features combinations. The simulation results have revealed that the best performance could be achieved by integrating unigram, bigram, and trigram features

A survey on deep learning in image polarity detection: Balancing generalization performances and computational costs

Deep convolutional neural networks (CNNs) provide an effective tool to extract complex information from images. In the area of image polarity detection, CNNs are customarily utilized in combination with transfer learning techniques to tackle a major problem: the unavailability of large sets of labeled data. Thus, polarity predictors in general exploit a pre-trained CNN as the feature extractor that in turn feeds a classification unit. While the latter unit is trained from scratch, the pre-trained CNN is subject to fine-tuning. As a result, the specific CNN architecture employed as the feature extractor strongly affects the overall performance of the model. This paper analyses state-of-the-art literature on image polarity detection and identifies the most reliable CNN architectures. Moreover, the paper provides an experimental protocol that should allow assessing the role played by the baseline architecture in the polarity detection task. Performance is evaluated in terms of both generalization abilities and computational complexity. The latter attribute becomes critical as polarity predictors, in the era of social networks, might need to be updated within hours or even minutes. In this regard, the paper gives practical hints on the advantages and disadvantages of the examined architectures both in terms of generalization and computational cost

Solanum lanceolatum (Solanaceae) in Sicily: A new alien species for the European flora

Solanum lanceolatum Cav. (Solanaceae) is a species native to Central America (Mexico, Belize, Guatemala and Panama), that has been found naturalized near Sutera and Porto Empedocle (Sicily). This is the first record in Italy and Europe

Teaching Simulations Supported by Artificial Intelligence in the Real World

Video conferencing has enabled synchronous communication in a classroom and created multi-sensory content to stimulate learners. Artificial intelligence involves complex equations that are better taught using a constructive pedagogy where students experiment with alternative ways of solving the same problem. Multiple-choice questions have high reliability and can easily reveal student skill levels in a quick way. The Australian Computer Society accreditation exercise ensures that the content for each subject serves as a flexible template for teaching. The geographical extent of the country requires the presence of multiple subordinate campuses affiliated to a main campus. Following the concept of strands, it was also necessary to show continuity in learning and assessments between the first- and second-year subjects. Student feedback for subjects with artificial intelligence-based simulations showed that several students found it difficult to understand lectures and assignments. Hence, to measure student learning, we introduced a Kahoot quiz during the recess of each lecture that students could join through their mobile phones from different campuses. Software project management is challenging for students with vision or attention-related disorders. We taught them how to use charts to visually observe variables and narrow down possible relationships before performing in-depth analysis. One of the main purposes of education is employability. Hence, greater context to real world industry examples was introduced into lectures

Temporal changes of vascular plant diversity in response to tree dieback in a mediterranean lowland forest

Palo Laziale wood is a small biotope of about 129 ha situated along the north coast of Rome. It is one of the last remaining patches of an ancient lowland floodplain forest that once covered the coastal area of the Lazio region. It contains several habitats and species of high conservation interest which has been included in the Natura2000 network. The forest suffered an impressive dieback event in 2003, coinciding with a particularly hot and dry summer. In the framework of an ecological restoration project (LIFE PRIMED LIFE17 NAT/GR/000511), a preliminary assessment of the biotic and abiotic components of the ecosystem was carried out, including a floristic analysis. This analysis was compared with that conducted in 1990 to assess whether there was any change in the species composition also following the forest dieback. Comparisons between biological forms, chorotypes and the Ellenberg indicators were also made in the analysis. The total flora of the site increased from 462 to 490 species. Moreover, there has been a turnover of species with the disappearance of some grassland and halophytic species and the appearance of allochthonous/ruderal and freshwater habitat species. Despite this, the flora remained unchanged in ecological terms, demonstrating a certain resilience of the plant species, confirming this approach to identify declining processes and support ecosystem-based restoration actions elsewhere

A study on text-score disagreement in online reviews

In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the same score (and vice-versa); and 2) detecting and analyzing the mismatches between the review content and the actual score may benefit both service providers and consumers, by highlighting specific factors of satisfaction (and dissatisfaction) in texts. To prove the intuitions, we adopt sentiment analysis techniques and we concentrate on hotel reviews, to find polarity mismatches therein. In particular, we first train a text classifier with a set of annotated hotel reviews, taken from the Booking website. Then, we analyze a large dataset, with around 160k hotel reviews collected from Tripadvisor, with the aim of detecting a polarity mismatch, indicating if the textual content of the review is in line, or not, with the associated score. Using well established artificial intelligence techniques and analyzing in depth the reviews featuring a mismatch between the text polarity and the score, we find that -on a scale of five stars- those reviews ranked with middle scores include a mixture of positive and negative aspects. The approach proposed here, beside acting as a polarity detector, provides an effective selection of reviews -on an initial very large dataset- that may allow both consumers and providers to focus directly on the review subset featuring a text/score disagreement, which conveniently convey to the user a summary of positive and negative features of the review target.Comment: This is the accepted version of the paper. The final version will be published in the Journal of Cognitive Computation, available at Springer via http://dx.doi.org/10.1007/s12559-017-9496-

The alien vascular flora of the Pantelleria Island National Park (Sicily Channel, Italy): new insights into the distribution of some potentially invasive species

Pantelleria is a volcanic island located in the Sicily Channel (Italy), between Sicily and Tunisia. The island, designated a National Park in 2016, hosts an interesting vascular flora of over 600 species including 9 narrow endemics. The island’s incredible biodiversity is, however, at risk due to anthropogenic influences, climate change, and, recently, the presence and spread of alien plant species. The Pantelleria alien flora has never been thoroughly investigated, probably because many non-native species were not yet present or so widespread on the island. Now, however, with the increased general awareness of the risks associated with invasive alien species, documentation of the presence of non-native species has been steadily increasing. In this study, field and literature research was carried out to investigate the alien flora of the island. Here, we report the status of a number of non-native plants with known invasive potential. Cenchrus setaceus (=Pennisetum setaceum) is reported for the first time as naturalized in the island with clear invasive behaviour, while, particularly remarkable for their invasive potential are other studied plants such as: Acacia saligna, Ailanthus altissima, Boheravia coccinea, Carpobrotus edulis, Leucaena leucocephala subsp. glabrata, Malephora crocea, Melia azedarach, Nicotiana glauca, Opuntia ficus-indica, Parkinsonia aculeata, Washingtonia robusta and a few others less important at the moment, but to be monitored. Although most taxa showed a relatively limited distribution, the trend is to observe an increased invasiveness, which indicates that they can potentially become invasive in Pantelleria as well in the next years or decades. Their limited current distribution suggests that these species are in the early stages of the general invasion curve, when intervention is feasible and most likely to succeed. Therefore, it is most prudent to prioritize management for as many potentially problematic nonnatives as possible, which will contribute greatly to the conservation of native species and ecosystems of Pantelleria. Prevention and management of invasive non-native species—both future arrivals and those already present—are necessary to preserve the peculiar volcanic landscape of Pantelleria, which was shaped by man over the last millennia