A method of detecting events in and clustering social media postings for display on a user system, the method comprising: retrieving, via an application programming interface API of a social media system over at least one first communication network, at least one posting of the social media system; determining whether the at least one posting has content referring to a predetermined time period; upon determining that the at least one posting has content referring to the predetermined time period, determining whether the at least one posting corresponds to an existing cluster of postings related to an event, wherein the determining whether the at least one posting corresponds to the existing cluster of postings related to the event utilizes a semantic-class-based approach including: assigning words of the at least one posting to a plurality of different semantic classes; for each semantic class, determining a similarity score between the words assigned to that semantic class for the at least one posting and words assigned to a corresponding semantic class for at least one existing clusters of postings; combining the similarity scores for the plurality of semantic classes to generate a combined similarity score; and determining whether the combined similarity score exceeds a predetermined threshold; upon determining that the at least one posting corresponds to the existing cluster of postings relating to the event, storing, in at least one database on a non-transitory machine-readable storage medium, the existing cluster of postings modified to include the at least one posting; and providing, via at least one second communication network (30, 34), a representation of the modified existing cluster of postings for display on a user system. retrieving, via an application programming interface API of a social media system over at least one first communication network, at least one posting of the social media system; determining whether the at least one posting has content referring to a predetermined time period; upon determining that the at least one posting has content referring to the predetermined time period, determining whether the at least one posting corresponds to an existing cluster of postings related to an event, wherein the determining whether the at least one posting corresponds to the existing cluster of postings related to the event utilizes a semantic-class-based approach including: assigning words of the at least one posting to a plurality of different semantic classes; for each semantic class, determining a similarity score between the words assigned to that semantic class for the at least one posting and words assigned to a corresponding semantic class for at least one existing clusters of postings; combining the similarity scores for the plurality of semantic classes to generate a combined similarity score; and determining whether the combined similarity score exceeds a predetermined threshold; assigning words of the at least one posting to a plurality of different semantic classes; for each semantic class, determining a similarity score between the words assigned to that semantic class for the at least one posting and words assigned to a corresponding semantic class for at least one existing clusters of postings; combining the similarity scores for the plurality of semantic classes to generate a combined similarity score; and determining whether the combined similarity score exceeds a predetermined threshold; upon determining that the at least one posting corresponds to the existing cluster of postings relating to the event, storing, in at least one database on a non-transitory machine-readable storage medium, the existing cluster of postings modified to include the at least one posting; and providing, via at least one second communication network (30, 34), a representation of the modified existing cluster of postings for display on a user system.