Recognizing causal elements and causal relations in the text is among the challenging issues in natural language processing (NLP), specifically in low-resource languages such as Persian. In this research, we prepare a causality human-annotated corpus for the Persian language. This corpus consists of 4446 sentences and 5128 causal relations. Three labels of Cause, Effect, and Causal mark are specified to each relation, if possible. We used this corpus to train a system for detecting causal elements’ boundaries. Also, we present a causality detection benchmark for three machine-learning methods and two deep learning systems based on this corpus. Performance evaluations indicate that our best total result is obtained through the CRF classifier, which provides an F-measure of 0. 76. In addition, the best accuracy (91. 4%) is obtained through the BiLSTM-CRF deep learning method

Automatic topic detection seems unavoidable in social media analysis due to big text data which their users generate. Clustering-based methods are one of the most important and up-to-date categories in topic detection. The goal of this research is to have a wide study on this category. Therefore, this paper aims to study the main components of clustering-based-topic-detection, which are embedding methods, distance metrics, and clustering algorithms. Transfer learning and consequently pretrained language models and word embeddings have been considered in recent years. Regarding the importance of embedding methods, the efficiency of five new embedding methods, from earlier to recent ones, are compared in this paper. To conduct our study, two commonly used distance metrics, in addition to five important clustering algorithms in the field of topic detection, are implemented by the authors. As COVID-19 has turned into a hot trending topic on social networks in recent years, a dataset including one-month tweets collected with COVID-19-related hashtags is used for this study. More than 7500 experiments are performed to determine tunable parameters. Then all combinations of embedding methods, distance metrics and clustering algorithms (50 combinations) are evaluated using Silhouette metric. Results show that T5 strongly outperforms other embedding methods, cosine distance is weakly better than other distance metrics, and DBSCAN is superior to other clustering algorithms.

The proposition “ Any essentially possible being requires a cause” must be considered as the precise wording of the causality principle. This is because according to principality of quiddity, the essential possibility is the criterion for quiddity’ s need of a cause, and according to the principality of existence, it is the sign for the of need of its existence to a cause. As for the attributes of the things, this principle is stated as “ the accidental is caused” . This is in contrast to “ the essential is not caused” which refers to the fact that the thing’ s essential attributes do not require a cause. The causality principle is itself a certain statement of the special mode of the principle of “ impossibility of preponderance without a preponderant” and is reduced to it. Thus, as far as self-evidence and non-self-evidence as well as provability and non-provability are concerned, it follows that principle; and as that principle is non-provable evident, so is the causality principle. From the principle of “ impossibility of preponderance without a preponderant” , another principle is derived as follows: the principle of “ impossibility of giving preponderance without a preponderant” which is the statement of the principle “ impossibility of preponderance without a preponderant” for the free-willed agent and his volitional actions, and is non-provable evident just like it.

causality is one of the most important philosophical problems which has undergone vast semantic changes in the course of history. This process has sometimes occurred in the mould of empirical explanation and sometimes in the mould of philosophical explanation. The vastness of such changes has led some thinkers to believe that there is a large semantic gap between metaphysical and natural kinds of causality, and the relationship between them is merely of the type of homonymy. The spread of this view among some philosophers and scholars has made any kind of agreement among them impossible. As a result, no comparative study can be carried out in these two fields concerning their shared concepts. Although some of the followers of the Transcendent Philosophy advocate the same view, the philosophical principles of Mulla Sadra have removed any kind of breach or borderline between these two fields and defines them in the same way. Accordingly, it can be claimed that natural causality is the degraded form of metaphysical causality and, thus, the unison of the two fields, their proximity to each other, and any interaction between them will be inevitable.

One of the main objectives of the study of the causes of historical events and important historical studies. In the present article in the first place, the four kinds of causalities that are used for historical explanation, that is, necessary and insufficient condition, sufficient and unnecessary condition, necessary and sufficient condition, and unnecessary and insufficient condition, are explained. History-based researchers of social sciences mainly search for specific results in one or few cases. Attempts have been made in the preset study to show that such historical analyses normally rely on counterfactual analysis. In other words, it is argued that if one tries to conduct a causal study of the past or evaluate a historical explanation, there is no other option than relying on counterfactual analysis. In the next step, the relationship between causal analysis with historical chain explanations has been studied. These analyses refer to the sequence or interconnected causal factors and explain historical events through interconnected events that unfold in the process of time.

Kant has attempted to response Hume's objections on the relation of cause and effect. In this regard, most exponents have concentrated on the second analogy and probably on the transcendental deduction; however, the right thing to do is to call attention to the most of components of criticism including the concept of time, metaphysical deduction, transcendental deduction, constitution-making, and especially the second analogy. In response to Hume, Kant has made an attempt to show the synthetic relation of the cause and the caused in the concept of object, and thereby to demonstrate the objective validity of causality. The paper in the first place presents an account and explanation of Kant's view and then deals with the criticism of it.